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We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.\n About the role As a Data Engineer supporting Billing \u0026 Payments Engineering, you'll join the Finance Data Engineering team and build the foundation for accurate, scalable billing and revenue data across Anthropic. You'll work closely with Billing Engineering, Finance and Accounting, as well as Product and other partners, to turn billing and payments data into reliable metrics, reporting and insights. You'll make sure teams have trustworthy data that scales with our growth, and you'll lead your own projects to enable self-serve insights that help teams make data-driven decisions.\n Responsibilities: • Partner with Billing Engineering, Finance and Accounting to understand their data and reporting needs, and translate them into technical requirements • Design, build and maintain data models and pipelines in dbt that transform raw billing, usage and payments data into canonical datasets • Own revenue data accuracy and reconciliation, making sure billing, usage and revenue data tie out across systems • Define success metrics for billing systems, and build the data models and monitoring to track them • Set high data integrity standards and SLAs for timely, accurate delivery of billing and revenue data • Share on-call and data operations responsibilities for Finance Data Engineering pipelines • Build dashboards and self-serve data products that track core metrics and deliver insights across the company • Champion best practices for dbt, data modeling and SQL • Influence the Billing Engineering roadmap from a data systems perspective • Become an expert in our data models and data architecture\n You may be a good fit if you have: • 5+ years of experience as a Data Engineer, Analytics Engineer or in a similar role • Expertise in SQL and Python, and in building multi-step data pipelines with tools like dbt • Experience with workflow orchestration tools like Airflow, and version control with GitHub • Familiarity with billing concepts such as invoicing, payments, credits, refunds and subscriptions, and experience working with data from billing systems • Experience building dashboards and reporting in tools like Hex for multiple cross-functional teams • A bias for action and urgency, without letting perfect be the enemy of the effective • A full-stack mindset: you do what it takes to solve a problem end to end, even when it goes beyond the original scope • Comfort with ambiguity, and the initiative to create clarity and keep work moving • A passion for Anthropic's mission of building helpful, honest and harmless AI\n Strong candidates may also have: • Experience partnering with billing, finance or accounting teams on revenue metrics and reconciliation • Experience building an analytics or data engineering function from an early stage\n The annual compensation range for this role is listed below. \n For sales roles, the range provided is the role’s On Target Earnings (\"OTE\") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.\n Annual Salary:\n $320,000 — $405,000 USD \n Logistics \n Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience\n Required field of study:  A field relevant to the role as demonstrated through coursework, training, or professional experience\n Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position\n Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.\n Visa sponsorship:  We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.\n We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. T","salary_min":320000,"salary_max":405000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["payments","data-pipeline","alignment","data-engineering","data-science"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5450099008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-12T19:03:03Z","expires_at":"2026-11-13T16:54:55.362957Z","created_at":"2026-10-14T15:17:21.640971Z","updated_at":"2026-10-14T16:54:55.365861Z","company_name":"Anthropic","company_slug":"anthropic","company_logo_url":"https://www.google.com/s2/favicons?domain=anthropic.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/a403cbfc-5ab6-4009-833a-3a9a90e4f43c"},{"id":"55139ac1-2db5-471c-b6aa-dbc4dc6745af","company_id":"a0000000-0000-0000-0000-000000000001","title":"Data Engineer, Product","slug":"data-engineer-product-96da0802","description":"About Anthropic \n Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.\n About the role As a Data Engineer on the Data Science \u0026 Analytics team, you'll build the foundation that lets analytics scale across Anthropic. You'll partner with Engineering, Product and other teams to turn raw data into reliable metrics, reporting and insights, and you'll make sure teams have accurate metrics for our consumer products from idea to launch. You'll also lead your own projects that make self-serve insights possible, so teams can make data-driven decisions.\n Responsibilities \n \n \n Understand, and where possible anticipate, the data needs of partner teams, and translate them into data models, reporting and technical requirements\n \n Define, build and manage key dbt pipelines that turn raw logs into canonical datasets\n \n Set data integrity standards and SLAs so data is delivered on time and accurately\n \n Build reliable dashboards that track core metrics and share insights across the company\n \n Build foundational data products, dashboards and tools that let self-serve analytics scale\n \n Partner with stakeholders to define and materialize metrics and analysis for new and evolving consumer products\n \n Shape Product teams' roadmaps from a data systems perspective\n \n Become an expert in our data models and data architecture\n \n You may be a good fit if you have \n \n \n Significant experience as a Data Engineer or in a similar Data Science \u0026 Analytics role, ideally partnering with Product leads to build and report on company-wide metrics\n \n A passion for Anthropic's mission of building helpful, honest and harmless AI\n \n Expertise building multi-step ETL jobs with tools like dbt, plus experience with workflow tools like Airflow and version control through GitHub\n \n Expertise in SQL and Python for turning data into accurate, clean data models\n \n Experience building reporting and dashboards in tools like Hex that serve multiple cross-functional teams\n \n A bias for action, and a sense of when \"good enough\" beats perfect\n \n An end-to-end mindset: you take ownership of solving a problem fully, even when that means picking up work beyond your usual scope\n \n Comfort with ambiguity, and a habit of creating clarity and forward progress\n \n Experience using AI to scale your own productivity and your team's without lowering the quality of the work\n \n Strong candidates may also have \n \n \n Experience building a data engineering (or similar) function from the ground up in an early-stage or fast-growing environment\n The annual compensation range for this role is listed below. \n For sales roles, the range provided is the role’s On Target Earnings (\"OTE\") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.\n Annual Salary:\n $320,000 — $405,000 USD \n Logistics \n Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience\n Required field of study:  A field relevant to the role as demonstrated through coursework, training, or professional experience\n Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position\n Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.\n Visa sponsorship:  We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.\n We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, ","salary_min":320000,"salary_max":405000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["data-pipeline","alignment","data-science","data-engineering"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5448481008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-09T17:00:40Z","expires_at":"2026-11-13T16:54:55.368278Z","created_at":"2026-10-14T15:17:21.646192Z","updated_at":"2026-10-14T16:54:55.371153Z","company_name":"Anthropic","company_slug":"anthropic","company_logo_url":"https://www.google.com/s2/favicons?domain=anthropic.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/55139ac1-2db5-471c-b6aa-dbc4dc6745af"},{"id":"103173eb-39e0-49ad-90d3-4aced5c995f3","company_id":"01048ffd-9864-41e0-a719-14b849fbcbcd","title":"Sr. Software Engineer (AI Data Engineering)","slug":"sr-software-engineer-ai-data-engineering-29df1a0b","description":"SpaceX was founded under the belief that a future where humanity is out exploring the stars is fundamentally more exciting than one where we are not. Today SpaceX is actively developing the technologies to make this possible, with the ultimate goal of enabling human life on Mars.\n SR. SOFTWARE ENGINEER (AI DATA ENGINEERING) \n Be a member of the Artificial Intelligence Data Engineering Software team, building AI-powered tools and automation that solve real engineering problems for our launch vehicles and spacecraft.\n Our team builds software that takes recurring, time-consuming work off engineers' plates so they can focus on hard engineering, from automated review of flight and test data to AI agents that help engineers prepare for missions and investigate anomalies. Your work will directly accelerate rapid reuse of the Falcon launch vehicle, support the world's largest satellite communication and AI constellations, and contribute to the development of the world's largest rocket capable of sending humans to Mars.\n You will work side-by-side with engineers across avionics, propulsion, structures, and more to find where their time goes and build tools that give it back, using agentic AI systems, MCP servers, RAG-based search, data pipelines over large telemetry datasets, and traditional automation where it is the right answer. You will own problems end-to-end: scoping the solution with the engineers who have the problem, rolling it out, measuring the time it saves, and maintaining it as the vehicle and processes evolve.\n Aerospace experience is not strictly required - we are looking for smart, motivated, collaborative engineers who love solving problems and want to make an impact on an inspiring mission.\n RESPONSIBILITIES: \n \n Partner directly with engineering teams to identify their most time-consuming, repetitive, or error-prone work, then design and build tools that automate it\n Build automation that processes large volumes of engineering data, including telemetry, hardware design databases, configuration files, and manufacturing and test records, to automate data review, flag anomalies, and surface insights\n Design agentic AI systems, multi-agent workflows, and MCP servers that let engineers query, analyze, and act on data across many internal systems\n Integrate tools into CI/CD pipelines, mission workflows, and review/sign-off processes so automation runs where engineers already work\n Build internal web dashboards that give engineers a clear view of mission status, open work, and data review results\n Rapidly prototype and iterate, then take tools to a production-grade, maintainable state\n Thoroughly test and validate all tools, including evaluating AI outputs against known-good results, so engineers can trust them in a flight-critical environment\n Prioritize work by return on investment and track the engineering hours saved\n \n BASIC QUALIFICATIONS: \n \n Bachelor's degree in computer science, data science, engineering, math, or physics; OR 4+ years of professional experience building automation for practical engineering use cases in lieu of a degree\n 5+ years of experience in software engineering with a focus on automation tools and/or AI integrations (professional and personal projects are applicable)\n 5+ years of programming experience in Python\n \n PREFERRED SKILLS AND EXPERIENCE: \n \n Track record of building tools that engineers or other end users actually adopted, including gathering requirements directly from users and iterating on their feedback\n Comfort processing and analyzing large engineering or scientific datasets (time-series telemetry, sensor data, logs, etc.) using tools such as pandas and NumPy\n Built code or configuration generators that turn a source of truth (design databases, spreadsheets, schemas) into validated outputs\n Hands-on work building complex agentic AI systems and multi-agent workflows, including prompt and context engineering, tool/function calling, and MCP servers or agent skills\n Ability to design evaluations for LLM-based tools, and the judgment to know when a deterministic script is a better fit than an AI model\n Skilled at integrating with many systems through REST APIs, and quickly learning unfamiliar internal tools and data sources\n Working knowledge of relational (PostgreSQL), non-relational, and vector databases, with strong SQL skills\n Full-stack experience building web applications or dashboards (e.g., React/TypeScript frontends with Python backends such as FastAPI or Flask)\n Proficiency developing on Linux, with a solid understanding of Git, testing, CI/CD, and monitoring\n Familiarity deploying containerized applications using Docker and Kubernetes\n Familiarity with hardware engineering concepts (electrical schematics and wiring, sensors, propulsion, controls, or test and manufacturing processes), or a background as a hardware or test engineer who moved into software\n Strong communication skills and ability to explain technical tradeoffs to engineers in other disc","salary_min":165000,"salary_max":265000,"location":"Hawthorne, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["llm","api-design","agents","embeddings","data-pipeline","data-engineering"],"apply_url":"https://boards.greenhouse.io/spacex/jobs/8880858002?gh_jid=8880858002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-09T00:39:29Z","expires_at":"2026-11-13T17:02:51.84726Z","created_at":"2026-10-14T15:24:54.877845Z","updated_at":"2026-10-14T17:02:51.850729Z","company_name":"SpaceX","company_slug":"spacex","company_logo_url":"https://www.google.com/s2/favicons?domain=spacex.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/103173eb-39e0-49ad-90d3-4aced5c995f3"},{"id":"a8096508-4339-4acb-af22-bfdb3dfc7cd2","company_id":"01048ffd-9864-41e0-a719-14b849fbcbcd","title":"Software Engineer (AI Data Engineering)","slug":"software-engineer-ai-data-engineering-93f6b849","description":"SpaceX was founded under the belief that a future where humanity is out exploring the stars is fundamentally more exciting than one where we are not. Today SpaceX is actively developing the technologies to make this possible, with the ultimate goal of enabling human life on Mars.\n SOFTWARE ENGINEER (AI DATA ENGINEERING) \n Be a member of the Artificial Intelligence Data Engineering Software team, building AI-powered tools and automation that solve real engineering problems for our launch vehicles and spacecraft.\n Our team builds software that takes recurring, time-consuming work off engineers' plates so they can focus on hard engineering, from automated review of flight and test data to AI agents that help engineers prepare for missions and investigate anomalies. Your work will directly accelerate rapid reuse of the Falcon launch vehicle, support the world's largest satellite communication and AI constellations, and contribute to the development of the world's largest rocket capable of sending humans to Mars.\n You will work side-by-side with engineers across avionics, propulsion, structures, and more to find where their time goes and build tools that give it back, using agentic AI systems, MCP servers, RAG-based search, data pipelines over large telemetry datasets, and traditional automation where it is the right answer. You will own problems end-to-end: scoping the solution with the engineers who have the problem, rolling it out, measuring the time it saves, and maintaining it as the vehicle and processes evolve.\n Aerospace experience is not strictly required - we are looking for smart, motivated, collaborative engineers who love solving problems and want to make an impact on an inspiring mission.\n RESPONSIBILITIES: \n \n Partner directly with engineering teams to identify their most time-consuming, repetitive, or error-prone work, then design and build tools that automate it\n Build automation that processes large volumes of engineering data, including telemetry, hardware design databases, configuration files, and manufacturing and test records, to automate data review, flag anomalies, and surface insights\n Design agentic AI systems, multi-agent workflows, and MCP servers that let engineers query, analyze, and act on data across many internal systems\n Integrate tools into CI/CD pipelines, mission workflows, and review/sign-off processes so automation runs where engineers already work\n Build internal web dashboards that give engineers a clear view of mission status, open work, and data review results\n Rapidly prototype and iterate, then take tools to a production-grade, maintainable state\n Thoroughly test and validate all tools, including evaluating AI outputs against known-good results, so engineers can trust them in a flight-critical environment\n Prioritize work by return on investment and track the engineering hours saved\n \n BASIC QUALIFICATIONS: \n \n Bachelor's degree in computer science, data science, engineering, math, or physics; OR 4+ years of professional experience building automation for practical engineering use cases in lieu of a degree\n 1+ years of experience in software engineering with a focus on automation tools and/or AI integrations (professional and personal projects are applicable)\n 1+ years of programming experience in Python\n \n PREFERRED SKILLS AND EXPERIENCE: \n \n Track record of building tools that engineers or other end users actually adopted, including gathering requirements directly from users and iterating on their feedback\n Comfort processing and analyzing large engineering or scientific datasets (time-series telemetry, sensor data, logs, etc.) using tools such as pandas and NumPy\n Built code or configuration generators that turn a source of truth (design databases, spreadsheets, schemas) into validated outputs\n Hands-on work building complex agentic AI systems and multi-agent workflows, including prompt and context engineering, tool/function calling, and MCP servers or agent skills\n Ability to design evaluations for LLM-based tools, and the judgment to know when a deterministic script is a better fit than an AI model\n Skilled at integrating with many systems through REST APIs, and quickly learning unfamiliar internal tools and data sources\n Working knowledge of relational (PostgreSQL), non-relational, and vector databases, with strong SQL skills\n Full-stack experience building web applications or dashboards (e.g., React/TypeScript frontends with Python backends such as FastAPI or Flask)\n Proficiency developing on Linux, with a solid understanding of Git, testing, CI/CD, and monitoring\n Familiarity deploying containerized applications using Docker and Kubernetes\n Familiarity with hardware engineering concepts (electrical schematics and wiring, sensors, propulsion, controls, or test and manufacturing processes), or a background as a hardware or test engineer who moved into software\n Strong communication skills and ability to explain technical tradeoffs to engineers in other discipli","salary_min":145000,"salary_max":195000,"location":"Hawthorne, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"mid","tags":["data-pipeline","llm","api-design","embeddings","agents","data-engineering"],"apply_url":"https://boards.greenhouse.io/spacex/jobs/8880868002?gh_jid=8880868002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-09T00:39:23Z","expires_at":"2026-11-13T17:02:51.635632Z","created_at":"2026-10-14T15:24:54.677511Z","updated_at":"2026-10-14T17:02:51.639609Z","company_name":"SpaceX","company_slug":"spacex","company_logo_url":"https://www.google.com/s2/favicons?domain=spacex.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/a8096508-4339-4acb-af22-bfdb3dfc7cd2"},{"id":"4708c050-c2b9-43f4-863a-aabad3dc6845","company_id":"92df3417-f362-4f1a-9406-e34d8013b283","title":"Senior Data Engineer, Product","slug":"senior-data-engineer-product-1e370dcb","description":"It all started with an idea at Block in 2013. Initially built to take the pain out of peer-to-peer payments, Cash App has gone from a simple product with a single purpose to a dynamic ecosystem, developing unique financial products, including Afterpay/Clearpay, to provide a better way to send, spend, invest, borrow and save to our 50+ million monthly active customers. We want to redefine the world’s relationship with money to make it more relatable, instantly available, and universally accessible. Today, Cash App has thousands of employees working globally across office and remote locations, with a culture geared toward innovation, collaboration and impact. We’ve been a distributed team since day one, and many of our roles can be done remotely from the countries where Cash App operates. No matter the location, we tailor our experience to ensure our employees are creative, productive, and happy.\n The Role \n As a Data Engineer, you will handle everything from data architecture and modeling to data pipeline tooling and dashboarding. You will enable a range of other engineering and business teams to make impactful business decisions by laying the foundation of our large and unique datasets that span across multiple products. This role will support the product data engineering team.\n The Product Data Engineering Team at Block builds and maintains the curated data foundation that powers all of Block's product lines — Cash App, Square, Afterpay, and Tidal. We transform raw event streams, transactional systems, and operational data into governed, tested, and reliable analytical assets across domains including banking, lending, commerce, investing, checkout, and AI assistants. We partner with Product, Engineering, Data Science, Machine Learning, and Applied AI teams to deliver the metrics, experimentation frameworks, and ML-ready datasets that enable Block's products to grow, improve, and serve customers at scale.\n  \n You Will \n \n Lead the creation and optimization of data models across eventing, customer-level, and process-level data, leveraging AI-assisted development tools to accelerate delivery.\n Take shared or independent technical ownership of critical data pipelines across Block — including foundational customer datasets, money transfer and movement pipelines, and the data infrastructure powering Block's experimentation platform.\n Build monitoring to assess data quality and lineage and further, build AI agents for false positive reduction and automated resolution. \n Participate in on-call rotation, monitor daily execution, diagnose and log issues, and fix business critical pipelines to ensure SLAs are met with internal stakeholders. Automate this process through AI agents to focus human effort on highest priority tasks.\n Work with non-technical partners and product teams to understand their needs, translate business requirements into applicable data requirements, and develop automated end-to-end solutions.\n \n  \n You Have \n \n A minimum of 10 years of related experience with a Bachelor’s degree; or 8 years and a Master’s degree; or equivalent experience.\n High proficiency in SQL, Python, and Dbt\n Experience designing medium-to-large data engineering solutions and responsible for the entire lifecycle of projects including scoping, design, development, testing, deployment, and documentation\n Experience with ETL scheduling technologies with dependency checking, such as Airflow or Prefect, as well as \n Experience in schema design and dimensional data modeling\n Experience with setting up data quality and data lineage monitoring\n Experience with data driven decisions through AI and agentic automation\n \n  \n Technologies We Use and Teach \n \n Snowflake\n Databricks\n Dbt\n Github\n Airflow\n Prefect\n Omni\n Terraform\n \n  \n We’re working to build a more inclusive economy where our customers have equal access to opportunity, and we strive to live by these same values in building our workplace. Block is an equal opportunity employer evaluating all employees and job applicants without regard to identity or any legally protected class. We will consider qualified applicants with arrest or conviction records for employment in accordance with state and local laws and “fair chance” ordinances. We believe in being fair, and are committed to an inclusive interview experience, including providing reasonable accommodations to disabled applicants throughout the recruitment process. We encourage applicants to share any needed accommodations with their recruiter, who will treat these requests as confidentially as possible. Want to learn more about what we’re doing to build a workplace that is fair and square? Check out our I+D page .\n While there is no specific deadline to apply for this role, U.S. roles are typically open for an average of 55 days before being filled by a successful candidate. Please refer to the date listed at the top of this job page for when this role was first posted.\n  \n Block takes a market-","salary_min":168300,"salary_max":252500,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["agents","payments","cloud","data-pipeline","data-science","data-engineering"],"apply_url":"http://block.xyz/careers/jobs/5442647008?gh_jid=5442647008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-08T21:28:47Z","expires_at":"2026-11-13T16:58:11.230731Z","created_at":"2026-10-14T15:21:51.255254Z","updated_at":"2026-10-14T16:58:11.233468Z","company_name":"Block","company_slug":"block","company_logo_url":"https://www.google.com/s2/favicons?domain=block.xyz\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/4708c050-c2b9-43f4-863a-aabad3dc6845"},{"id":"074ea5ff-c6b6-449e-9c6e-56c3323c5341","company_id":"d8e15a46-b80d-4228-8e7b-34f00357f377","title":"Lead Data Engineer","slug":"lead-data-engineer-5087a7dc","description":"Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale — unleashing the potential of businesses and people. The Elastic Search AI Platform, used by more than 50% of the Fortune 500, brings together the precision of search and the intelligence of AI to enable everyone to accelerate the results that matter. By taking advantage of all structured and unstructured data — securing and protecting private information more effectively — Elastic’s complete, cloud-based solutions for search, security, and observability help organizations deliver on the promise of AI.\n What is The Role \n \n  \n We're looking for a Lead Data Engineer to join our Data Engineering \u0026 Architecture team. In this role, you'll help grow a Data Platform that makes it easier for teams across our company to work with data confidently and  effectively . Your work will directly support our business goals not just by keeping data flowing, but by turning it into something people can actually use and trust. \n \n  \n This is a great opportunity for someone who enjoys both the technical craft of data engineering and the human side of it: collaborating with partners, sharing knowledge, and helping others get more out of the tools and systems you build  together . \n  \n \n What You Will Be Doing \n  \n \n You'll design, maintain, and improve the pipelines and infrastructure that power our data platform. Day to day, that means working across the full data lifecycle — from ingestion and streaming to transformation and delivery — using tools like Apache Airflow, Spark, Iceberg, Kafka, Flink, and dbt Labs. \n \n  \n Beyond the technical work, you'll spend meaningful time with stakeholders to understand what they need and help define how data should flow across systems. That includes co-creating data contracts, writing clear documentation, and guiding teammates on how to get the most out of the platform. \n \n  \n A few other things you'll take on: \n \n \n Monitor and refine pipeline performance and refine processes to keep things running smoothly. \n \n Use Terraform to provision and manage resources on Google Cloud Platform (GCP). \n \n Help steward the platform by reviewing code and ensuring good practices and standard processes are followed. \n \n Process access requests and support compliance with platform policies. \n \n What You Bring \n \n \n 8+ years of experience in data engineering or related roles \n \n Experience with Apache Airflow for orchestrating data workflows \n \n Experience with Spark, Flink, Kafka, and dbt Labs for data processing and transformation \n \n Understanding of Apache Iceberg for data table formats and data warehouse and lakehouse strategies \n \n Skilled in using Terraform for infrastructure-as-code deployments \n \n Proficient in programming languages, particularly Bash, Python, and SQL \n \n Knowledge of database systems, including OLAP, OLTP, Document, and Vector databases \n \n Experience with Google Cloud Platform (GCP) for cloud resource management \n \n Bonus: Proven experience with data security and access controls for SOX Compliant data \n \n Bonus: Experience and knowledge of the Elastic stack \n \n Compensation for this role is in the form of base salary.  This role does not have a variable compensation component.   \n The typical starting salary range for new hires in this role is listed below.  In select locations (including Seattle WA, Los Angeles CA, the San Francisco Bay Area CA, and the New York City Metro Area), an alternate range may apply as specified below.  \n These ranges represent the lowest to highest salary we reasonably and in good faith believe we would pay for this role at the time of this posting.  We may ultimately pay more or less than the posted range, and the ranges may be modified in the future.   \n An employee's position within the salary range will be based on several factors including, but not limited to, relevant education, qualifications, certifications, experience, skills, geographic location, performance, and business or organizational needs. \n Elastic believes that employees should have the opportunity to share in the value that we create together for our shareholders. Therefore, in addition to cash compensation, this role is currently eligible to participate in Elastic's stock program.  Our total rewards package also includes a company-matched 401k with dollar-for-dollar matching up to 6% of eligible earnings, along with a range of other benefits offered with a holistic emphasis on employee well-being. \n The typical starting salary range for this role is:\n $113,100 — $178,900 USD \n The typical starting salary range for this role in the select locations listed above is:\n $135,900 — $215,100 USD \n Additional Information - We Take Care of Our People \n As a distributed company, diversity drives our identity. Whether you’re looking to launch a new career or grow an existing one, Elastic is the type of company where you can balance grea","salary_min":135900,"salary_max":215100,"location":"United States","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["embeddings","search","data-pipeline","data-engineering"],"apply_url":"https://jobs.elastic.co/jobs?gh_jid=8247144\u0026gh_jid=8247144","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-06T18:39:27Z","expires_at":"2026-11-13T16:57:57.540935Z","created_at":"2026-10-14T15:21:37.619706Z","updated_at":"2026-10-14T16:57:57.545432Z","company_name":"Elastic","company_slug":"elastic","company_logo_url":"https://www.google.com/s2/favicons?domain=www.elastic.co\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/074ea5ff-c6b6-449e-9c6e-56c3323c5341"},{"id":"e0be16b1-242b-4a96-b22e-736f0755cae8","company_id":"5a1ac926-3bb4-40bb-b952-7dc959ae1820","title":"Tech Lead Manager, Machine Learning, Growth and Marketing   ","slug":"tech-lead-manager-machine-learning-growth-and-marketing-527e3a43","description":"About the Role \n Chime’s Data Science and Machine Learning team is building models, services, and platforms that transform how millions of users manage and grow their financial lives. We are looking for a hands-on Tech Lead Manager with deep technical expertise in machine learning and data science, particularly within the Growth and Marketing domain. Beyond technical proficiency, we value creativity, user empathy, and strong collaboration. \n As a Tech Lead Manager within our Growth and Marketing team, you will lead a talented group of data scientists and machine learning engineers to develop innovative growth and marketing models. These models will provide critical insights into acquiring, retaining and growing Chime members, broaden access to credit, and ensure financial inclusivity. You will play a pivotal role in creating innovative, ground-up products while driving the development of cutting-edge acquisition and retention models and solutions. If you are passionate about marketing, growth, customer acquisition and retention models, this role could be a great fit for you. \n In this role, you can expect to \n \n Lead and inspire a high-performing team of data scientists and ML engineers, ensuring the successful development and deployment of machine learning solutions for customer acquisition, conversion and retention. \n Drive strategic direction for ML initiatives in marketing, engagement, and growth by identifying opportunities where AI/ML can optimize our customer funnel. \n Oversee the end-to-end development of machine learning models such as lifetime value prediction, churn risk modeling, customer segmentation, marketing attribution, referral recommendations, and personalized communications. \n Collaborate cross-functionally with marketing, product, growth, and engineering teams to align machine learning initiatives with business objectives. \n Leverage transactional and behavioral data to enhance customer targeting, optimize acquisition spend, and improve retention strategies. \n Establish ML best practices, including model development, validation, deployment, and monitoring, ensuring scalability and business impact. \n Advocate for a data-driven culture, partnering with business leaders to drive strategic decisions through experimentation and predictive analytics. \n Stay ahead of industry trends, bringing cutting-edge AI/ML techniques into our marketing and growth strategies. \n \n To thrive in this role, you have \n \n 7+ years of experience developing machine learning models for marketing and growth, from inception to production, with a focus on customer acquisition, engagement, and retention. \n 5+ years of experience leading data science teams, with a proven track record of mentoring, coaching, and driving impactful machine learning solutions. \n Strong expertise in marketing and growth analytics, including experience with customer segmentation, LTV modeling, churn prediction, referral systems, and multi-touch attribution. \n Deep understanding of AI/ML techniques, including classification, clustering, reinforcement learning, optimization, deep learning, and NLP for customer engagement. \n Hands-on experience deploying machine learning models in real-world production environments, integrating with marketing tech stacks and growth platforms. \n Strong product intuition with the ability to work iteratively in a fast-paced, cross-functional environment. \n M.S. or Ph.D. in Machine Learning, Computer Science, Statistics, or a related STEM field. \n Proficiency in Python and SQL, with experience in building ML pipelines and wrangling large-scale data. \n Experience with modern ML and data engineering technologies, such as AWS, Kafka, Airflow, Redis, MySQL, Postgres, Spark, Snowflake, Looker. \n Exceptional communication and stakeholder management skills, with the ability to partner effectively with marketing, growth, product, and engineering teams. \n \n #LI-DA1 #LI-Onsite \n Below is the base salary offered for this role and level of experience. Full-time employees may also be eligible for bonus(es), competitive equity, and benefits. For commissioned roles, the base salary listed in this job description does not include incentive/variable pay. The actual base salary offered may be higher, depending on your location, skills, qualifications, and experience.\n Wage Notice\n $199,000 — $275,000 USD \n A little about us \n At Chime, we believe that everyone can achieve financial progress. We created Chime—a financial technology company, not a bank*—on the premise that core banking services should be helpful, easy, and free. Through our user-friendly tools and intuitive platforms, we empower our members to take control of their finances and work towards their goals. Whether it's starting a savings account, purchasing a first car or home, launching a business, or pursuing higher education, we're proud to have helped millions unlock their financial potential. \n We're a team of problem solvers, dreamers, and builders with one ","salary_min":199000,"salary_max":275000,"location":"San Francisco, CA","workplace":"remote","remote_scope":"unknown","job_type":"full-time","experience_level":"lead","tags":["nlp","deep-learning","payments","reinforcement-learning","data-engineering","machine-learning"],"apply_url":"https://boards.greenhouse.io/chime/jobs/8864214002?gh_jid=8864214002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-02T18:01:52Z","expires_at":"2026-11-13T17:03:12.47807Z","created_at":"2026-10-14T15:25:16.005996Z","updated_at":"2026-10-14T17:03:12.481159Z","company_name":"Chime","company_slug":"chime","company_logo_url":"https://www.google.com/s2/favicons?domain=chime.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/e0be16b1-242b-4a96-b22e-736f0755cae8"},{"id":"36809570-dc01-41d5-87b5-5f68feb0ac68","company_id":"714f360f-a244-487d-b3f0-0c43518a9e66","title":"Sr. Staff Software Engineer, Product ML Infrastructure","slug":"sr-staff-software-engineer-product-ml-infrastructure-8c8c843d","description":"About Pinterest: \n Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.\n Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the  flexibility to do your best work. Creating a career you love? It’s Possible.\n At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI.\n Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here .\n Sr. Staff Software Engineer, Product ML Infrastructure \n Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.\n At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI.\n Pinterest’s Product ML Infrastructure (PMLI) team enables fast, safe, and efficient delivery of AI/ML solutions across Ads and Core critical products. We build unified data, training, feature, and inference infrastructure; this role will set technical direction across model training and serving, with a focus on GPU efficiency and large-scale ranking systems.\n What you’ll do: \n \n Set the technical vision and roadmap for model training and serving across PMLI, with reusable interfaces to data and feature infrastructure.\n Lead architectures for distributed training, fine-tuning, distillation, evaluation, and high-scale CPU/GPU inference.\n Improve efficiency across data loading, distributed execution, GPU kernels and memory, compilation, quantization, scheduling, and capacity.\n Build reliable, observable platforms with strong quality guarantees and training/serving consistency.\n Partner with Ads and Core AI/ML teams to productionize features and models safely at Pinterest scale.\n Drive cross-organizational architecture decisions, migrations, and operational standards; mentor senior engineers and raise the engineering bar.\n Use AI-assisted development and analysis to accelerate prototyping, performance diagnosis, and validation while maintaining rigorous correctness and data safeguards.\n \n What we’re looking for: \n \n A track record of setting technical strategy and delivering company-wide infrastructure initiatives in ambiguous environments.\n Deep expertise in distributed ML systems, including production experience with both large-scale training and online inference.\n Strong GPU performance knowledge, such as profiling, distributed execution, kernel and memory optimization, compilation, or quantization.\n Experience with AI/ML modeling, recommender systems, Ads ranking, retrieval, feature platforms, or similarly demanding ML workloads.\n Strong systems programming and design skills in C++, Java, or Python.\n High ownership and sound judgment in reliability, security, cost, and operational excellence.\n Demonstrated ability to use AI to improve speed and critically evaluate AI-assisted work, with accountability for correctness, quality, and sensitive data.\n Bachelor’s degree in Computer Science, Engineering, a related field, or equivalent experience.\n \n  \n Relocation Statement: \n \n This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.\n \n  \n In-Office Requirement Statement: \n \n We recognize that the ideal environment for work is situational and may differ across departments. What this looks like day-to-day can vary based on the needs of each organization or role.\n This role will need to be in the office for in-person collaboration 1–2 times per quarter and therefore needs to be within a commutable distance of our Palo Alto, CA or San Francisco, CA office.\n \n  \n #LI-REMOTE\n #LI-AG8\n At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. The position is also eligible for equity. Fina","salary_min":245402,"salary_max":429454,"location":"Palo Alto, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["distributed-systems","fine-tuning","data-engineering","machine-learning","infrastructure"],"apply_url":"https://www.pinterestcareers.com/jobs/?gh_jid=8046860","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-30T19:41:55Z","expires_at":"2026-11-13T16:57:51.190315Z","created_at":"2026-10-14T15:21:31.42495Z","updated_at":"2026-10-14T16:57:51.193465Z","company_name":"Pinterest","company_slug":"pinterest","company_logo_url":"https://www.google.com/s2/favicons?domain=www.pinterest.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/36809570-dc01-41d5-87b5-5f68feb0ac68"},{"id":"3c2bf5e5-f474-4f7f-95c6-6195b666fa2c","company_id":"714f360f-a244-487d-b3f0-0c43518a9e66","title":"Principal Engineer, AI Platform","slug":"principal-engineer-ai-platform-d8f92b91","description":"About Pinterest: \n Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.\n Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the  flexibility to do your best work. Creating a career you love? It’s Possible.\n At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI.\n Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here .\n Millions of people across the world come to Pinterest to find new ideas every day. It’s where they get inspiration, dream about new possibilities and plan for what matters most. Our mission is to help those people find their inspiration and create a life they love. As a Pinterest employee, you’ll be challenged to take on work that upholds this mission and pushes Pinterest forward.\n As a Principal Engineer on the AI Platform team, you'll help architect the infrastructure that powers both Generative AI and Recommender Systems across Pinterest's entire product suite. Our team builds the end-to-end engines for petabyte-scale data orchestration, model training and fine-tuning, and high-performance inference, ensuring our models scale seamlessly to hundreds of millions of inferences per second in service of over 600 million monthly active users.\n  \n What you’ll do: \n \n Set the technical vision and roadmap for the Pinterest AI Platform, aligning with business priorities and long-term company strategy.\n Drive cross-functional strategic initiatives that advance our platform capabilities across:\n \n Generative AI: multimodal data management, post-training, evaluation, and batch/online inference.\n Recommender Systems: feature stores, training infra, and large-scale high performance inference.\n AI-powered tools that automate the user experience across our platforms, connecting every stage of the AI/ML lifecycle to enhance productivity and accelerate development.\n \n Cultivate a collaborative and inclusive culture where every team member feels welcome and empowered, and provide candid, constructive feedback that accelerates individual and team growth.\n \n  \n What we’re looking for: \n \n Deep expertise in AI/ML infrastructure and distributed systems: Hands-on experience designing, building, and operating highly available, production-grade systems at large scale; strong technical judgment; and proficiency in at least one of C++, Java, or Rust.\n Proven track record of company-wide impact: Experience leading cross-organizational initiatives, navigating ambiguity, defining technical strategy, influencing architecture decisions, and aligning cross-functional partners and executives around a shared direction.\n Strong ownership and a high engineering bar: Sets and upholds high standards for engineering quality, integrity, and accountability, and takes end-to-end ownership of outcomes.\n Bachelor's degree in Computer Science or a related field.\n \n  \n Relocation Statement : \n \n This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.\n \n  \n In-Office Requirement Statement : \n \n We recognize that the ideal environment for work is situational and may differ across departments. What this looks like day-to-day can vary based on the needs of each organization or role.\n This role will need to be in the office for in-person collaboration 1-2 times per quarter and therefore needs to be in a commutable distance from one of the following offices: Palo Alto, CA or San Francisco, CA. \n \n #LI-REMOTE\n #LI-AH2\n At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. The position is also eligible for equity. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise.\n Information regarding the culture at Pinterest and benefits available for this position can be found here . \n US based applicants only\n $242,634 — $499,541 USD \n Our Commitment to Inclusion: \n Pinterest is an equal opportunity employer and makes employment decisions on the basis of merit. We want to have the best qualified people in every job. All qualified","salary_min":242634,"salary_max":499541,"location":"San Francisco, CA","workplace":"remote","remote_scope":"unknown","job_type":"full-time","experience_level":"principal","tags":["distributed-systems","generative-ai","fine-tuning","data-engineering"],"apply_url":"https://www.pinterestcareers.com/jobs/?gh_jid=7683977","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-22T18:14:17Z","expires_at":"2026-11-13T16:57:51.115782Z","created_at":"2026-10-14T15:21:31.357846Z","updated_at":"2026-10-14T16:57:51.121183Z","company_name":"Pinterest","company_slug":"pinterest","company_logo_url":"https://www.google.com/s2/favicons?domain=www.pinterest.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/3c2bf5e5-f474-4f7f-95c6-6195b666fa2c"},{"id":"c2c087b1-a7e5-4f21-8fd7-1666857a9619","company_id":"ac154286-ea56-4ef4-ab48-5ffaa9596888","title":"Senior AI/ML Engineer, Applications \u0026 Automation","slug":"senior-aiml-engineer-applications-automation-adf357a8","description":"We are seeking a Senior AI/ML Engineer to design, build, deploy, and evolve AI models, agents, and workflow automation for clinical terminology and content operations. This hands-on role combines AI/ML development with production ownership, taking models and agents from experimentation to reliable production use. The ideal candidate has experience with large language models, agent frameworks, retrieval-augmented generation, and the infrastructure and controls required to operate AI systems reliably.\n","salary_min":150000,"salary_max":200000,"location":"United States","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"senior","tags":["agents","healthcare","rag","llm","data-engineering","machine-learning"],"apply_url":"https://jobs.lever.co/imo-online/84751a15-4271-4453-80b3-bfdfa2e63354/apply","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-14T20:44:53.204Z","expires_at":"2026-11-13T17:00:18.728644Z","created_at":"2026-10-14T15:23:52.626731Z","updated_at":"2026-10-14T17:00:18.733674Z","company_name":"IMO Health","company_slug":"imo-health","company_logo_url":"https://www.google.com/s2/favicons?domain=imohealth.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/c2c087b1-a7e5-4f21-8fd7-1666857a9619"},{"id":"a1c5b877-b5a2-4c4d-bd4b-fc533e9768a4","company_id":"714f360f-a244-487d-b3f0-0c43518a9e66","title":"Principal Engineer, Big Data Platform","slug":"principal-engineer-big-data-platform-955de11d","description":"About Pinterest: \n Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.\n Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the  flexibility to do your best work. Creating a career you love? It’s Possible.\n At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI.\n Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here .\n We’re looking for a principal software engineer to lead the next generation of data infrastructure at Pinterest which powers mission critical big data and AI applications. You’ll be working on some of the most exciting big data and AI open source technologies (Flink, Spark, Kubernetes, etc.), at the scale of exabytes of data to help Pinners discover and do what they love.\n  \n What you’ll do: \n \n Lead the strategy and technical direction of Pinterest’s data infrastructure for big data and AI applications\n Build and scale data infra frameworks and infrastructure to process petabytes-scale datasets, including compute engines, job management, resource management, scheduling and remote shuffling\n Work with internal customers on critical business use cases that rely on big data \n Provide thought leadership to the entire company on how data should be processed and stored more reliably, quickly and efficiently at scale\n Contribute to the team’s technical vision and long-term roadmap\n \n  \n What we’re looking for: \n \n 12+ years of industry experience with a proven track record of technical excellence\n 8+ years of experience of building and support large scalable Kubernetes or big data platform\n Deep knowledge of big data / ML technologies (e.g. Flink, Spark, Presto, Kubernetes, Ray, PyTorch/TensorFlow)\n Proficiency in one or more programming languages (Java, Go, Scala, Python)\n Experiences in Kubernetes and AWS technologies\n Exceptional collaboration skills with cross-functional partners, with the ability to navigate ambiguity, make tradeoffs, and keep stakeholders aligned on priorities and progress.\n Bachelor’s degree in Computer Science, a related technical field, or equivalent experience. \n \n In-Office Requirement Statement: \n \n We let the type of work you do guide the collaboration style. That means we're not always working in an office, but we continue to gather for key moments of collaboration and connection.\n This role will need to be in the office for in-person collaboration 1-2 times/quarter and therefore can be situated anywhere in the country. \n \n  \n Relocation Statement: \n \n This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.\n \n #LI-REMOTE\n #LI-CL5 \n At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. The position is also eligible for equity. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise.\n Information regarding the culture at Pinterest and benefits available for this position can be found here . \n US based applicants only\n $242,634 — $499,541 USD \n Our Commitment to Inclusion: \n Pinterest is an equal opportunity employer and makes employment decisions on the basis of merit. We want to have the best qualified people in every job. All qualified applicants will receive consideration for employment without regard to race, color, ancestry, national origin, religion or religious creed, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, age, marital status, status as a protected veteran, physical or mental disability, medical condition, genetic information or characteristics (or those of a family member) or any other consideration made unlawful by applicable federal, state or local laws. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you require a medical or religious accommodation during the job application process, please complete  this form for support.\n  \n By submitting this application, I certify that al","salary_min":242634,"salary_max":499541,"location":"San Francisco, CA","workplace":"remote","remote_scope":"unknown","job_type":"full-time","experience_level":"principal","tags":["pytorch","tensorflow","cloud","data-engineering"],"apply_url":"https://www.pinterestcareers.com/jobs/?gh_jid=7683981","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-02T16:50:22Z","expires_at":"2026-11-13T16:57:51.124069Z","created_at":"2026-09-03T13:39:42.804269Z","updated_at":"2026-10-14T16:57:51.127782Z","company_name":"Pinterest","company_slug":"pinterest","company_logo_url":"https://www.google.com/s2/favicons?domain=www.pinterest.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/a1c5b877-b5a2-4c4d-bd4b-fc533e9768a4"},{"id":"7aa92365-6b3e-4f51-a168-2674aa7d8a06","company_id":"76c63eb7-c307-4322-8c2b-c20216feec49","title":"Senior/Staff Data Engineer","slug":"senior-data-infrastructure-engineer-96f0f9f8","description":"Get to Know Us\n\nHorizon3 is a fast-growing, remote cybersecurity company dedicated to the mission of enabling organizations to proactively find and fix and verify exploitable attack vectors before criminals exploit them. Our flagship product, the NodeZeroTM platform, delivers production-safe autonomous pentests and other key assessment operations that scale across the largest internal, external, cloud, and hybrid cloud environments. NodeZero has been adopted by organizations of all sizes, from small educational institutions to government agencies and Global 100 enterprises. It is used by ITOps/SecOps teams, consulting pentesters, and MSSPs and MSPs. \n\nWe are a fusion of former U.S. Special Operations cyber operators, startup engineers, and formerly frustrated cybersecurity practitioners. We're committed to helping solve our common security problems: ineffective security tools, false positives resulting in alert fatigue, blind spots, \"checkbox” security culture, cybersecurity skills shortage, and the long lead time and expense of hiring outside consultants. Collectively, we are a team of learn it alls, committed to a culture of respect, collaboration, ownership, and results.\n\n\n\nWe are seeking a Senior or Staff Data Engineer to design, build, and own the data platform underneath our business-critical pipelines. Today the team supports account provisioning, product analytics, and the pipelines feeding our warehouse and Tableau reporting. You will help expand this into a globally deployed data platform spanning the warehouse, orchestration, and BI across multiple regions\n\nYou will:\n\n - Design, build, and maintain business-critical data pipelines, including data ingestion and AWS Glue/Spark jobs feeding the warehouse and Tableau.\n\n - Build and operate core data infrastructure: the data warehouse, orchestration, and BI/reporting platform, deployed across multiple regions.\n\n - Help evaluate and shape our warehouse strategy, including lakehouse platforms such as Databricks.\n\n - Define and evolve batch or event-driven contracts between producer and consumer teams, reasoning through batch vs. streaming, CDC, reprocessing, and multi-tenant/multi-region trade-offs.\n\n - Design and evolve warehouse schemas and data models.\n\n - Build observability into pipelines and platform components.\n\n - Drive work across producer and consumer teams, communicate clearly, and own outcomes end to end.\n\nWhat You’ll Bring\n\n - Strong software engineering craft: clean, correct, maintainable code with solid data-structure and problem-solving fundamentals.\n\n - Deep understanding of distributed systems and data architecture: pipeline and platform design, batch vs. streaming, CDC, event contracts, multi-tenant and multi-region trade-offs, reprocessing, and observability.\n\n - Fluent SQL and strong data-modeling skills, including designing schemas for a warehouse your team owns.\n\n - Experience owning production data infrastructure end to end.\n\n - Strong collaboration and ownership across dependent teams.\n\n - 7+ years of professional experience in data engineering, infrastructure engineering, or backend software engineering.\n\n - Bachelor’s degree in Computer Science or a related field, or equivalent practical experience.\n\n\n\nRequired Tech Stack Experience\n\n - Experience with cloud-based data platforms and distributed data processing (e.g., AWS Glue, Databricks, Snowflake, or Spark-based pipelines)\n\n - Tableau or a comparable BI platform.\n\n - SQL and Python.\n\n - Workflow orchestration tooling such as Apache Airflow, Dagster or similar\n\n \n\nPerks of Horizon3\n\n - Inclusive Team: We value diversity and promote an inclusive culture where everyone can thrive.\n\n - Growth Opportunities: Be part of a dynamic and growing team with numerous career development opportunities.\n\n - Innovative Culture: Work in a collaborative environment that encourages creativity and out-of-the-box thinking.\n\n - Hybrid \u0026 Remote Work: We embrace a mix of remote and hybrid work models depending on role and location, including our Chicago office, where some roles require regular in-office presence.\n\n - Competitive Compensation: We offer competitive salary, equity and benefits. Our benefits include health, vision \u0026 dental insurance for you and your family, a flexible vacation policy, and generous parental leave.\n\n\n\nCompensation and Values\n\nAt Horizon3, we believe that our people are our greatest asset, and our compensation philosophy reflects this core value. We are committed to fostering an environment where all employees feel valued, respected, and rewarded for their contributions. Our compensation structure is designed to be fair, competitive, and transparent, ensuring that every team member is recognized and compensated equitably across roles, levels, and locations.\n\nIn accordance with various State’s transparency regulations, we provide the following salary range information for this position:\n\n - Base salary range: $199,000 - $270,000 annually. The exact salary will be ","salary_min":199000,"salary_max":270000,"location":"Remote (US)","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["cloud","distributed-systems","security","data-pipeline","data-engineering"],"apply_url":"https://jobs.ashbyhq.com/horizon3ai/4651e6b3-a8b5-484f-ac87-5b6ca04581d1/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-27T16:58:31.284Z","expires_at":"2026-11-13T16:56:49.823663Z","created_at":"2026-08-29T13:37:07.314282Z","updated_at":"2026-10-14T16:56:49.826842Z","company_name":"Horizon3 AI","company_slug":"horizon3-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=horizon3.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/7aa92365-6b3e-4f51-a168-2674aa7d8a06"},{"id":"d4653f80-c2d2-4f90-b750-70a300947a71","company_id":"861968d1-d9f8-4217-9873-ce4b24851abc","title":"Manager of Data Engineering \u0026 Delivery (Data Science Production Engineering)","slug":"manager-of-data-science-production-engineering-data-engineering-delivery-a1a2ddc4","description":"This is an exciting opportunity to lead a Data Engineering \u0026 Delivery (DED) team at Natera, a global leader in precision medicine and genomics testing.  As a Manager of the DED team inside our Data Science Production Engineering (DSPE) department, you will have the opportunity to work with Natera's diverse and ultra-large data sets (up to PB size), develop innovative solutions with the latest information and cloud technologies, and make real impact by providing timely, accurate, and robust data products and data delivery/automation systems to support Natera's Lab Operations and Genetic Counselor/Lab Director teams, and ultimately impact patients' medical outcomes.\n PRIMARY RESPONSIBILITIES:  \n Leadership \n \n Lead a Data Engineering \u0026 Delivery (DED) team, collectively develop and maintain the data infrastructure, data ingestion solutions, ETL pipelines, robust data products, and data delivery solutions, for both production support and DSPE internal applications.\n Manage the Data Engineering \u0026 Delivery (DED) team, to achieve the timely and efficient delivery of robust data products and systems that can meet DSPE business needs and project requirements.\n Measure, report, and maintain/improve operational effectiveness.\n Train and coach team members on new technologies, procedures, and guidelines/best practices.\n \n Technical \n \n Lead the Data Engineering \u0026 Delivery (DED) team, collectively develop and maintain the data infrastructure, data ingestion solutions, ETL pipelines, robust data products, and data delivery solutions, for both production support and DSPE internal applications\n Translate DSPE's business needs and project requirements into technical specifications and implementation plans.\n Working with DSPE leadership teams, create design documents that can be efficiently implemented and maintained, for data system architecture, data ETL pipeline, data delivery solution, and other data systems/tools/components.\n Contribute to key development, testing, deployment, validation, maintenance, and update activities on data products and data systems/tools/components, as well as data delivery tasks.\n \n Quality, Compliance, and Documentation \n \n Improve and enforce operating procedures for compliance, quality, and efficiency.\n Create training materials, and contribute to training activities, on DSPE Data Engineering \u0026 Delivery (DED) team owned data products and data systems.\n \n Cross-Functional \n \n Engage proactively and directly with internal and external stakeholders to align development roadmaps, resolve dependencies, and exchange performance metrics.\n Represent the Data Engineering \u0026 Delivery (DED) team in stakeholder meetings.\n \n QUALIFICATIONS: \n \n Masters degree in Statistics, Data Science, Bioinformatics, Computer Science, Mathematics, Management Science, Operational Research, or other related fields. Doctorate degrees are a plus.\n Minimal 5 years of relevant industry experience for candidates with a Master's Degree.  Minimal 2 years of relevant industry experience for candidates with a Doctorate degree.\n Minimal 2 years of working experience in a highly regulated environment, e.g., CLIA and/or FDA compliant settings.\n Minimal 2 years of management experience leading a Data Engineering team, a Data Production/Delivery team, or a Data Analytics team, with demonstrable evidence of leadership and team management skills.\n \n KNOWLEDGE, SKILLS, AND ABILITIES: \n \n Strong proficiency in SQL and Python programming languages. Proficiency in R is a plus.\n Proficiency in data analysis and statistical techniques.\n Proficiency in data visualization tools (e.g., Tableau, Power BI, AWS QuickSight).\n Strong SQL skills in developing robust and maintainable queries to extract and/or aggregate data from complex data sources.\n Attention to detail and a commitment to data accuracy.\n Proficiency in building data products, e.g., data aggregation, extraction, transformation, and QC. Past working experience in dbt is a plus.\n Excellent problem-solving and critical-thinking abilities.\n Working knowledge of genomics and bioinformatics workflows. Human genetics knowledge is a plus.\n Proficiency in Git workflow and version control systems like GitHub and/or GitLab.\n Working experience with healthcare data, electronic health records (EHR), and clinical terminology is a plus.\n Ability to work collaboratively in a cross-functional team environment.\n Good documentation practices and coding style.\n Strong verbal and written communication skills.\n Strong interpersonal skills.\n Strong integrity.\n \n Compensation \u0026 Total Rewards  \n This range reflects a good-faith estimate of the base pay we reasonably expect to offer at the time of  hire. Final compensation will vary based on experience, qualifications, and internal equity considerations. \n This position is also eligible for additional compensation and benefits through Natera’s robust Total Rewards program, including: \n \n \n Annual performance incentive bonus \n \n Long-term equity awar","salary_min":139900,"salary_max":174900,"location":"San Carlos, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["cloud","healthcare","data-pipeline","data-engineering","data-science"],"apply_url":"https://job-boards.greenhouse.io/natera/jobs/6150570004","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-21T20:13:10Z","expires_at":"2026-11-13T16:58:37.966082Z","created_at":"2026-08-25T18:29:44.00758Z","updated_at":"2026-10-14T16:58:37.970559Z","company_name":"Natera","company_slug":"natera","company_logo_url":"https://www.google.com/s2/favicons?domain=natera.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/d4653f80-c2d2-4f90-b750-70a300947a71"},{"id":"2def9ded-6b75-4209-9cee-cda6c10334c1","company_id":"861968d1-d9f8-4217-9873-ce4b24851abc","title":"Manager of Data Engineering \u0026 Delivery (Data Science Production Engineering)","slug":"manager-of-data-science-production-engineering-data-engineering-delivery-a8bbb51b","description":"This is an exciting opportunity to lead a Data Engineering \u0026 Delivery (DED) team at Natera, a global leader in precision medicine and genomics testing.  As a Manager of the DED team inside our Data Science Production Engineering (DSPE) department, you will have the opportunity to work with Natera's diverse and ultra-large data sets (up to PB size), develop innovative solutions with the latest information and cloud technologies, and make real impact by providing timely, accurate, and robust data products and data delivery/automation systems to support Natera's Lab Operations and Genetic Counselor/Lab Director teams, and ultimately impact patients' medical outcomes.\n PRIMARY RESPONSIBILITIES:  \n Leadership \n \n Lead a Data Engineering \u0026 Delivery (DED) team, collectively develop and maintain the data infrastructure, data ingestion solutions, ETL pipelines, robust data products, and data delivery solutions, for both production support and DSPE internal applications.\n Manage the Data Engineering \u0026 Delivery (DED) team, to achieve the timely and efficient delivery of robust data products and systems that can meet DSPE business needs and project requirements.\n Measure, report, and maintain/improve operational effectiveness.\n Train and coach team members on new technologies, procedures, and guidelines/best practices.\n \n Technical \n \n Lead the Data Engineering \u0026 Delivery (DED) team, collectively develop and maintain the data infrastructure, data ingestion solutions, ETL pipelines, robust data products, and data delivery solutions, for both production support and DSPE internal applications\n Translate DSPE's business needs and project requirements into technical specifications and implementation plans.\n Working with DSPE leadership teams, create design documents that can be efficiently implemented and maintained, for data system architecture, data ETL pipeline, data delivery solution, and other data systems/tools/components.\n Contribute to key development, testing, deployment, validation, maintenance, and update activities on data products and data systems/tools/components, as well as data delivery tasks.\n \n Quality, Compliance, and Documentation \n \n Improve and enforce operating procedures for compliance, quality, and efficiency.\n Create training materials, and contribute to training activities, on DSPE Data Engineering \u0026 Delivery (DED) team owned data products and data systems.\n \n Cross-Functional \n \n Engage proactively and directly with internal and external stakeholders to align development roadmaps, resolve dependencies, and exchange performance metrics.\n Represent the Data Engineering \u0026 Delivery (DED) team in stakeholder meetings.\n \n QUALIFICATIONS: \n \n Masters degree in Statistics, Data Science, Bioinformatics, Computer Science, Mathematics, Management Science, Operational Research, or other related fields. Doctorate degrees are a plus.\n Minimal 5 years of relevant industry experience for candidates with a Master's Degree.  Minimal 2 years of relevant industry experience for candidates with a Doctorate degree.\n Minimal 2 years of working experience in a highly regulated environment, e.g., CLIA and/or FDA compliant settings.\n Minimal 2 years of management experience leading a Data Engineering team, a Data Production/Delivery team, or a Data Analytics team, with demonstrable evidence of leadership and team management skills.\n \n KNOWLEDGE, SKILLS, AND ABILITIES: \n \n Strong proficiency in SQL and Python programming languages. Proficiency in R is a plus.\n Proficiency in data analysis and statistical techniques.\n Proficiency in data visualization tools (e.g., Tableau, Power BI, AWS QuickSight).\n Strong SQL skills in developing robust and maintainable queries to extract and/or aggregate data from complex data sources.\n Attention to detail and a commitment to data accuracy.\n Proficiency in building data products, e.g., data aggregation, extraction, transformation, and QC. Past working experience in dbt is a plus.\n Excellent problem-solving and critical-thinking abilities.\n Working knowledge of genomics and bioinformatics workflows. Human genetics knowledge is a plus.\n Proficiency in Git workflow and version control systems like GitHub and/or GitLab.\n Working experience with healthcare data, electronic health records (EHR), and clinical terminology is a plus.\n Ability to work collaboratively in a cross-functional team environment.\n Good documentation practices and coding style.\n Strong verbal and written communication skills.\n Strong interpersonal skills.\n Strong integrity.\n The pay range is listed and actual compensation packages are based on a wide array of factors unique to each candidate, including but not limited to skill set, years \u0026 depth of experience, certifications and specific office location. This may differ in other locations due to cost of labor considerations.\n Remote USA\n $127,200 — $159,000 USD \n OUR OPPORTUNITY \n Natera™ is a global leader in cell-free DNA (cfDNA) testing, dedicated to oncology, w","salary_min":127200,"salary_max":159000,"location":"Remote (US)","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"senior","tags":["healthcare","cloud","data-pipeline","data-engineering","data-science"],"apply_url":"https://job-boards.greenhouse.io/natera/jobs/6137669004","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-21T20:13:08Z","expires_at":"2026-11-13T16:58:37.974527Z","created_at":"2026-08-25T18:29:44.00289Z","updated_at":"2026-10-14T16:58:37.978128Z","company_name":"Natera","company_slug":"natera","company_logo_url":"https://www.google.com/s2/favicons?domain=natera.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/2def9ded-6b75-4209-9cee-cda6c10334c1"},{"id":"ea21c070-6402-4604-8a11-b603165cac3a","company_id":"bce4421e-5b23-4e76-b067-fc8a82064141","title":"Data Engineer (SE / Sr SE)","slug":"data-engineer-se-sr-se-ee21f58c","description":"PlusAI is a Physical AI company pioneering AI-based virtual driver software for factory-built autonomous trucks. Headquartered in Silicon Valley with operations in the United States and Europe, Plus was named by Fast Company as one of the World’s Most Innovative Companies. Partners including TRATON GROUP’s Scania, MAN, and International brands, Hyundai Motor Company, Iveco Group, Bosch, and DSV are working with Plus to accelerate the deployment of next-generation autonomous trucks. If you’re ready to make a huge impact and drive the future of autonomy, Plus is looking for talented individuals to join its fast-growing teams.\n\n\nKnowing how well our virtual driver drives — and why it fell short — is what lets us ship with confidence. In this role, you will own that loop end to end: the metrics that quantify driving performance, the pipelines that compute them at fleet scale, the analysis that turns them into judgments about autonomy behavior — including where on the map that behavior changes — the data and tooling that gate software releases, and the agentic workflows that take a detected issue from triage to a proposed fix. You will work primarily in Python across large-scale data processing, geospatial analytics, evaluation frameworks, and LLM-powered automation. We welcome engineers from data engineering, analytics, geospatial, evaluation, or robotics backgrounds; prior autonomous-vehicle experience is helpful but not required.\nWe are open to candidates at either the Engineer or Software Engineer level. Level will be determined by experience, technical depth, scope of ownership, and demonstrated impact. You do not need experience with every technology in our stack; we value strong fundamentals, ownership, and the ability to learn.\nResponsibilities:\nDefine and compute driving performance metrics — covering safety, comfort, progress, interventions, and compliance — and build the scalable pipelines that evaluate them consistently across fleet and simulation data\nAnalyze road-test and simulation data in depth to identify trends, regressions, and anomalies in autonomy behavior, and turn them into clear findings that engineering teams act on\nBuild geospatial analytics over fleet driving data: map-matched metrics, route and corridor performance, location-based clustering of events and issues, and geographic coverage analysis that shows where the virtual driver performs well and where it struggles\nBuild the data foundations and tooling for release management, including release-over-release comparisons, readiness and gating criteria, and traceable evidence supporting release decisions\nBuild AI agentic workflows that triage detected issues at scale — clustering and deduplicating failures, attributing root cause, routing to the right owners, and proposing fixes with supporting evidence for engineering review\nEnsure that your work is performed in accordance with the company's Quality Management System (QMS) requirements and contribute to continuous improvement efforts\n","salary_min":130000,"salary_max":200000,"location":"San Jose, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["llm","agents","robotics","data-engineering","infrastructure"],"apply_url":"https://jobs.lever.co/plus-2/cd1e5dca-104e-4429-af74-ee6da17596cb/apply","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-10T19:55:36.074Z","expires_at":"2026-11-13T17:00:42.151033Z","created_at":"2026-08-25T18:32:31.372506Z","updated_at":"2026-10-14T17:00:42.153728Z","company_name":"Plus","company_slug":"plus","company_logo_url":"https://www.google.com/s2/favicons?domain=plus.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/ea21c070-6402-4604-8a11-b603165cac3a"},{"id":"abba779f-44e8-4ffd-8b33-f3c5486ad2bb","company_id":"f8de0913-0ef7-4e72-a9cf-81f8513ec624","title":"Software Engineer, Data Engineering","slug":"software-engineer-data-engineering-56e2f4f4","description":"FieldAI’s Irvine team is where embodied AI meets real robots, real sensors, and real field deployments. Based in the heart of Southern California’s robotics ecosystem, we build risk-aware, reliable, field-ready AI systems that solve the hardest problems in robotics and unlock the full potential of embodied intelligence. If you want your work to ship, get tested on hardware, and improve through real deployments, Irvine is the place. We go beyond typical data-driven approaches or pure transformer-only architectures, combining rigorous engineering with learning systems proven in globally deployed solutions that deliver results today and get better every time our robots run in the field.\n","salary_min":115000,"salary_max":170000,"location":"Irvine, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"mid","tags":["robotics","platform","infrastructure","data-engineering"],"apply_url":"https://jobs.lever.co/field-ai/e3b7bac7-5410-44bb-964c-02815fbd0c97/apply","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-01T01:03:02.312Z","expires_at":"2026-11-13T17:00:38.145568Z","created_at":"2026-08-25T18:32:29.469657Z","updated_at":"2026-10-14T17:00:38.148183Z","company_name":"Field AI","company_slug":"field-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=field.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/abba779f-44e8-4ffd-8b33-f3c5486ad2bb"},{"id":"9d404039-fcb8-449d-a86d-505b2458db6e","company_id":"92df3417-f362-4f1a-9406-e34d8013b283","title":"Senior Data Engineer, Risk","slug":"senior-data-engineer-risk-8b142407","description":"It all started with an idea at Block in 2013. Initially built to take the pain out of peer-to-peer payments, Cash App has gone from a simple product with a single purpose to a dynamic ecosystem, developing unique financial products, including Afterpay/Clearpay, to provide a better way to send, spend, invest, borrow and save to our 50+ million monthly active customers. We want to redefine the world’s relationship with money to make it more relatable, instantly available, and universally accessible. Today, Cash App has thousands of employees working globally across office and remote locations, with a culture geared toward innovation, collaboration and impact. We’ve been a distributed team since day one, and many of our roles can be done remotely from the countries where Cash App operates. No matter the location, we tailor our experience to ensure our employees are creative, productive, and happy.\n The Role \n As a Data Engineer you will handle everything from data architecture and modeling to data pipeline tooling and dashboarding. You will enable other compliance and risk teams to make impactful business decisions by laying the foundation of our large and unique datasets that span across multiple products. This role will support compliance or risk product data engineering teams.\n The Compliance Data Engineering team at Block supports the detection  and reporting of suspicious financial crimes activity across Cash App, Square, and Afterpay. We work globally with partners in business, engineering, counsel, and product to provide a safe user experience for our customers while minimizing and potentially eliminating bad activity on our platform.\n The Risk Product Data Engineering team at Block builds reliable data foundations that help protect customers across Cash App, Square, and Afterpay. We partner with product, engineering, compliance, and legal teams to support risk detection, reporting, instrumentation, and ML-ready datasets across critical domains including identity, account access, eligibility, controls, and disputes.\n You Will \n \n Lead the creation and optimization of existing data models through AI code generation on eventing, customer level, and process level data.\n Standardize business and product metric definitions in curated and optimized datasets, and develop data dictionaries and other related documentation.\n Build monitoring to assess data quality and lineage and on top build AI agents for false positive reduction and automated resolution. \n Participate in on-call rotation, monitor daily execution, diagnose and log issues, and fix business critical pipelines to ensure SLAs are met with internal stakeholders. Automate this process through AI agents to focus human effort on highest priority tasks.\n Work with non-technical partners and product teams to understand their needs, translate business requirements into applicable data requirements, and come up with automated end-to-end solutions.\n \n You Have \n \n A minimum of 10 years of related experience with a Bachelor’s degree; or 8 years and a Master’s degree; or equivalent experience.\n High proficiency in SQL, Python, and Dbt\n Experience designing medium-to-large data engineering solutions and responsible for the entire lifecycle of projects including scoping, design, development, testing, deployment, and documentation\n Experience with ETL scheduling technologies with dependency checking, such as Airflow or Prefect, as well as \n Experience in schema design and dimensional data modeling\n Experience with setting up data quality and data lineage monitoring\n Experience with data driven decisions through AI and agentic automation\n \n Technologies We Use and Teach \n \n Snowflake\n Databricks\n Dbt\n Github\n Airflow\n Prefect\n Omni\n Terraform\n \n  \n We’re working to build a more inclusive economy where our customers have equal access to opportunity, and we strive to live by these same values in building our workplace. Block is an equal opportunity employer evaluating all employees and job applicants without regard to identity or any legally protected class. We will consider qualified applicants with arrest or conviction records for employment in accordance with state and local laws and “fair chance” ordinances. We believe in being fair, and are committed to an inclusive interview experience, including providing reasonable accommodations to disabled applicants throughout the recruitment process. We encourage applicants to share any needed accommodations with their recruiter, who will treat these requests as confidentially as possible. Want to learn more about what we’re doing to build a workplace that is fair and square? Check out our I+D page .\n While there is no specific deadline to apply for this role, U.S. roles are typically open for an average of 55 days before being filled by a successful candidate. Please refer to the date listed at the top of this job page for when this role was first posted.\n  \n Block takes a market-based approach to p","salary_min":168300,"salary_max":252500,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["payments","data-pipeline","cloud","agents","code-generation","data-engineering"],"apply_url":"http://block.xyz/careers/jobs/5281312008?gh_jid=5281312008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-02T17:34:01Z","expires_at":"2026-11-13T16:58:11.234718Z","created_at":"2026-07-03T14:09:16.691517Z","updated_at":"2026-10-14T16:58:11.237448Z","company_name":"Block","company_slug":"block","company_logo_url":"https://www.google.com/s2/favicons?domain=block.xyz\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/9d404039-fcb8-449d-a86d-505b2458db6e"},{"id":"a9e674c4-8acb-4aab-859f-e10cac573d16","company_id":"a0000000-0000-0000-0000-000000000001","title":"Data Engineer, Safeguards","slug":"p-data-engineer-safeguards-372ad660","description":"About Anthropic \n Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.\n About the role \n As a Data Engineer on the Safeguards team, you will build the data foundations that keep our AI systems safe. The Safeguards team works to monitor models, prevent misuse, and ensure user well-being — and doing that well requires robust, reliable data infrastructure.\n In this role, you will design and build the pipelines, warehousing solutions, and analytical tooling that power our safety and trust efforts at scale. You'll work closely with engineers, data scientists, and policy teams to ensure the Safeguards organization has the data it needs to detect abuse patterns, measure the effectiveness of safety interventions, and make informed decisions about model behavior and enforcement. This is a high-impact role where your work directly supports Anthropic's mission to develop AI that is safe and beneficial.\n Key responsibilities \n \n Design, build, and maintain scalable data pipelines that support safety monitoring, abuse detection, and enforcement workflows\n Develop and optimize data models and warehousing solutions to enable efficient analysis of large-scale usage and safety data\n Build and maintain dashboards and reporting infrastructure that give Safeguards teams visibility into model behavior, misuse patterns, and enforcement outcomes\n Collaborate with engineers to integrate data from multiple sources — including model outputs, user reports, and automated classifiers — into a unified analytical layer\n Implement data quality frameworks, monitoring, and alerting to ensure the reliability of safety-critical data\n Partner with research teams to surface data insights that inform model improvements and safety interventions\n Develop self-service data tooling that enables stakeholders to explore safety data and generate reports independently\n Contribute to data governance practices, including access controls, retention policies, and privacy-compliant data handling\n \n Minimum qualifications \n \n Proficiency in SQL and Python, with hands-on experience building and maintaining ETL/ELT pipelines\n Experience with cloud data platforms such as BigQuery, Redshift, Snowflake, or similar\n Experience with modern data stack tools such as dbt, Airflow, Spark, or similar orchestration and transformation frameworks\n Experience building dashboards and data visualizations using tools such as Looker, Tableau, or Metabase\n Ability to communicate clearly and translate complex data concepts for both technical and non-technical audiences\n \n Preferred qualifications \n \n 8+ years of experience in data engineering, analytics engineering, or a related role\n Comfort contributing across the stack and picking up work outside your immediate scope when the situation calls for it\n Background in trust and safety, integrity, fraud, or abuse detection data systems\n Experience with large-scale event streaming systems such as Kafka, Pub/Sub, or Kinesis\n Experience building data infrastructure that supports ML model monitoring or evaluation\n Familiarity with data privacy and compliance frameworks such as GDPR, CCPA, or similar\n Background in statistical analysis or experience working closely with data scientists\n A genuine interest in the societal implications of AI and in making AI systems safer\n The annual compensation range for this role is listed below. \n For sales roles, the range provided is the role’s On Target Earnings (\"OTE\") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.\n Annual Salary:\n $320,000 — $405,000 USD \n Logistics \n Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience\n Required field of study:  A field relevant to the role as demonstrated through coursework, training, or professional experience\n Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position\n Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.\n Visa sponsorship:  We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.\n We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing impos","salary_min":320000,"salary_max":405000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["mlops","data-pipeline","alignment","data-engineering","data-science"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5240422008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-01T20:26:10Z","expires_at":"2026-11-13T16:54:55.373285Z","created_at":"2026-07-03T06:27:20.399206Z","updated_at":"2026-10-14T16:54:55.375941Z","company_name":"Anthropic","company_slug":"anthropic","company_logo_url":"https://www.google.com/s2/favicons?domain=anthropic.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/a9e674c4-8acb-4aab-859f-e10cac573d16"},{"id":"13525a3f-edee-40f6-89a0-fca61b3c9118","company_id":"e3915539-5a8f-4461-9f26-06366a918674","title":"Product Data Engineer","slug":"product-data-engineer-c7f0a1f5","description":"Anduril Industries is a defense technology company with a mission to transform U.S. and allied military capabilities with advanced technology. By bringing the expertise, technology, and business model of the 21st century’s most innovative companies to the defense industry, Anduril is changing how military systems are designed, built and sold. Anduril’s family of systems is powered by Lattice OS, an AI-powered operating system that turns thousands of data streams into a realtime, 3D command and control center. As the world enters an era of strategic competition, Anduril is committed to bringing cutting-edge autonomy, AI, computer vision, sensor fusion, and networking technology to the military in months, not years.\n ABOUT THE TEAM \n Anduril is seeking a Product Data Engineer to join our Configuration Management team. As a Product Data Engineer you will work closely with the leaders of critical Anduril programs to manage a highly dynamic and fast-paced design, engineering, and manufacturing environment. The Product Data Engineer will have a massive impact on capturing and defining the baseline for a program’s requirements, design, testing, manufacturing, and sustainment data structures (requirements baseline, EBOM, MBOM, SOM, BOP). WHAT YOU'LL DO \n \n Be a partner to Product and Program teams by:\n Working with Anduril system, design, and manufacturing engineers to generate, populate and submit configuration item change requests.\n Preparing critical analyses to support change requests while maintaining configuration integrity and traceability (item dependency analyses, test analyses, effectivity plans, inventory disposition analyses etc.)\n Supporting the execution and implementation of change notices across system engineering, design engineering, manufacturing engineering, and supply chain domains.\n Identifying and executing continuous improvement opportunities by building data-driven perspectives of the full product configuration landscape.\n Be the leader of critical configuration management activities and forums by:\n Supporting configuration managers in managing critical program technical forums (Test Review Board, Change Control Board etc.).\n Working with program teams to prepare for critical technical forums (the Change Review Board, the Change Control Board) including preparing of business cases, test data, effectivity plans, inventory disposition plans, etc.\n Documenting and distributing conclusions, decisions emerging from configuration management forums.\n Conduct periodic product configuration record audits by:\n Supporting configuration management reviews and audits, including FCA/PCA and providing direction before, during and after the events to prevent or resolve issues.\n Reconciling released bills of materials against baseline bills of materials by confirming all variances have signed-off change notices.\n Reconciling product as-built-records against released bills of materials by confirming all variances have quality deviations.\n Identifying, analyzing resolving non-conformances; finding and resolving root-causing failure modes.\n Be an expert resource for the Product Teams for Engineering Release and Change Management processes and standards by:\n Using Teamcenter software to manage Engineering changes, including part revisions, EBOM/MBOM/SBOM updates, documentation modifications, and associated workflows.\n Providing guidance and support to Engineering teams in configuring the Engineering, Manufacturing, and Service Bills of Materials (EBOM, MBOM, SBOM)\n Supporting Configuration Managers and Engineers in defining and maintaining configurable product data sets (i.e., 150% BOMs, product variant dictionaries and schema).\n Being a Teamcenter super-user and able to train product team users on workflows.\n Be part of the team defining the future of digital engineering at Anduril by:\n Partnering with engineering teams to set requirements and identify improvement opportunities in existing ways of working by creating tools or enhancing existing workflows.\n Building an end-to-end digital thread that maintains an accurate product definition, system by system, from the definition of requirements to the as maintained record.\n Identifying and piloting opportunities to leverage Anduril’s AI capabilities tools to unlock increased speed, accuracy, and efficiency within Anduril’s configuration management activities.\n \n REQUIRED QUALIFICATIONS \n \n 3+ years of configuration analysis or equivalent experience.\n 3+ years of demonstrated experience working in high complexity and high-rate production environments (aerospace, automotive, security systems, medical devices, nuclear).\n Familiar with configuration management principles and practices (EIA649/C, MIL-HDBK-61B).\n Experience with product lifecycle management (PLM) and/or data management toolsets for configuration management of complex products\n Possess high attention to detail and strong organizational skills.\n Excellent written and verbal communication skills","salary_min":112000,"salary_max":149000,"location":"Irvine, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"mid","tags":["computer-vision","payments","cloud","data-engineering"],"apply_url":"https://boards.greenhouse.io/andurilindustries/jobs/5150089007?gh_jid=5150089007","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-06-29T18:01:58Z","expires_at":"2026-11-13T16:57:16.051406Z","created_at":"2026-06-30T14:06:43.416674Z","updated_at":"2026-10-14T16:57:16.054312Z","company_name":"Anduril","company_slug":"anduril","company_logo_url":"https://www.google.com/s2/favicons?domain=anduril.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/13525a3f-edee-40f6-89a0-fca61b3c9118"},{"id":"13a6bdb5-cf40-4e9e-85f4-af6c9c89b189","company_id":"63839083-85dd-4aa0-b128-254fc82866e5","title":"Senior / Staff Software Engineer, ML Datasets \u0026 Data Pipelines","slug":"senior-staff-software-engineer-ml-datasets-data-pipelines-d6def817","description":"Waabi, founded by AI visionary Raquel Urtasun, is the leader in Physical AI. With a world-class team, we're unlocking the next era of autonomous transportation with technology that's powering commercial autonomous trucks and robotaxis. Waabi is backed by and partners with world leaders in AI, automotive, logistics, and deep tech.\n \nWith offices in Toronto, San Francisco, Dallas, and Pittsburgh, Waabi is growing quickly and looking for diverse, innovative and collaborative candidates who want to impact the world in a positive way. To learn more visit: www.waabi.ai\n\n\nAs a Senior/Staff Software Engineer embedded within our Autonomy \u0026 Algorithms team, you will build the scalable ML data pipelines necessary to train and evaluate Waabi’s autonomous driving platform. Working closely with world-renowned scientists and engineers, you will solve complex data challenges to accelerate our launch of fully driverless vehicles.\n \nYou Will..\nDesign and implement data pipelines using real-world driving data and Waabi World (our high-fidelity simulator) to train and evaluate deep learning models.\nOptimize data formats, caching, and dataloading to drive highly efficient ML training and evaluation at scale.\nImprove data sampling and composition for deep data introspection to track model performance and uncover critical edge-case scenarios.\nChampion engineering excellence by writing high-quality, well-structured, and rigorously tested code.\nHelp drive project roadmap planning, prioritization, and delivery.\nQualifications:\nBS or MS in Computer Science, Machine Learning, or a related technical field, with 4+ years of industry experience.\nProficiency in Python and strong software engineering fundamentals, including experience with deep learning frameworks such as PyTorch, TensorFlow, or JAX.\nHands-on experience building distributed ETL and data processing pipelines.\nDirect experience managing ML pipelines, including dataset management, dataloading, and optimization.\nStrong understanding of cloud job orchestration, monitoring, and instrumentation best practices.\nA collaborative, open-minded approach with a passion for tackling hard problems in autonomous technology and a strong willingness to mentor others.\n \nBonus Points:\nExperience with optimizing large scale distributed training pipelines and/or highly optimized ML inference pipelines.  \nExperience with MapReduce (Apache Hadoop/Spark) or orchestration frameworks (Apache Airflow, Apache Beam, Google Cloud Dataflow, AWS Step Functions).\nExperience solving data challenges specific to autonomous driving.\nFamiliarity with linear algebra (projections, transforms) and 3D geometry.\nExperience working with multimodal sensor data (e.g., LiDAR, RADAR, camera).\n","salary_min":148000,"salary_max":260000,"location":"Toronto, Canada","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["deep-learning","distributed-systems","autonomous-vehicles","pytorch","tensorflow","cloud","data-pipeline","data-engineering"],"apply_url":"https://jobs.lever.co/waabi/81ed817e-cb56-45f8-aac6-e645610798da/apply","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-03-26T16:35:32.938Z","expires_at":"2026-11-13T16:56:19.844409Z","created_at":"2026-04-13T09:41:54.316786Z","updated_at":"2026-10-14T16:56:19.847457Z","company_name":"Waabi","company_slug":"waabi","company_logo_url":"https://www.google.com/s2/favicons?domain=waabi.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/13a6bdb5-cf40-4e9e-85f4-af6c9c89b189"}],"page":1,"per_page":20,"total":97,"total_is_exact":true,"total_pages":5}