Senior Research Engineer, Olmo

Persons in these roles are expected to work from our offices in Seattle. On-site requirements vary based on position and team. If you have questions about on-site work arrangements for this role, please ask your recruiter. Our base salary range is $170,000 - $220,000, and in addition we have generous bonus plans to provide a competitive compensation package.  Who We Are:  We are a non-profit AI institute, focused on developing foundational AI research and innovation to deliver real-world impact through large-scale open models, data, and artifacts (e.g., Olmo , Tulu , Molmo ).   We unite the best and brightest scientific and engineering minds to explore the potential of truly open AI. Through  our efforts, including the pioneering Olmo releases, we endeavor to empower academics, researchers, and AI developers more broadly to advance language models and generative AI models. Through close collaboration, we rapidly identify, define, and act on the most exciting and promising new ideas in AI.   Our team engages in a broad range of AI research, including pre-training and post-training language models, curating data to enhance AI across different modalities, and developing novel methodologies to push the field forward. We study and evaluate AI models both theoretically and empirically, aiming to advance their capabilities. Additionally, we create impactful real-world applications, such as in scientific synthesis. Our goal is to develop state-of-the-art models that excel in scientific discovery, reasoning, and factual recall. Who You Are:  You are a talented, hands-on engineer who thrives in a fast-paced environment, is self-directed, a team player, and knows how to get things done. You have a deep knowledge of Python, infrastructure, and a strong understanding of modern deep learning, natural language processing, language models, and the inner workings of the transformer architecture. You can translate high-level goals into concrete research and implementation steps, set an approach, follow through, and present results. When it’s time to explain your ideas, you bring clarity to complex technical issues. You use these skills to create real-world benefits for researchers and other practitioners, and you are excited to help advance our effort to create the best-performing open AI model. Your Next Challenge: You will be a part of the core team of research and machine learning engineers working on the infrastructure, architecture, modeling and training of Olmo (Open Language Model) at all stages: pre-training, mid-training, post-training and all emerging paradigms. In this role you will be owning the design and implementation of the systems that train these models. You will be responsible for building scalable machine learning pipelines as we push the boundaries of large language modeling research. You will be collaborating with colleagues inside and outside your own team, but you are responsible for a feature or experiment from start to finish, from conception to implementation. The essential functions include, but are not limited to the following: Building infrastructure to facilitate the next generation of LLM research Optimizing training and inference for language models Triaging between experiments and executing on the most impactful Supporting and collaborating with an open-source community Bridging the gap between cutting-edge research and a widely adopted product Bringing software engineering best practices to a research environment Releasing your contributions back to the broader community in the form of open source software, model releases, and additions to Ai2’s public API and open research datasets, as well as technical reports What You’ll Need:  Expertise at building ML infrastructure - having 4+ years of industry experience building infrastructure that handles data preprocessing/transformation and model training, evaluation, inference, and deployment Deep experience in the complete model development cycle, including data set construction, training, tuning, evaluation, performance profiling, and monitoring Knowledge of modern deep learning and natural language processing techniques Strong software engineering skills, particularly around building performant systems and debugging At-home with hands-on programming – must have experience with Python and PyTorch/Jax/Tensorflow. We expect you to be the kind of engineer who can pick up a new programming language, library, or API as needed without it being a big deal. Familiarity working with cloud compute resources (e.g. AWS) and containerization (e.g. Docker) Strong collaboration and communication skills - our environment is small and collaborative, and we'd like you to thrive while working closely with others, sometimes with complementary skills/perspectives Bonus qualifications: Advanced degree in Data Science/CS/EE/Applied Mathematics/Statistics/ML/NLP or related fields and/or relevant and equivalent e