Sr. AI Engineer (Speech)

About Dialpad Dialpad is the AI platform for customer experience, built to resolve customer problems in real time across voice and digital. Our AI agents learn from your best human agents and improve with every interaction, helping organizations understand their customers, deliver better experiences, increase operational efficiencies, and build a lasting competitive advantage. Unlike legacy systems built to route and answer, or standalone agentic bot vendors built to deflect, Dialpad was built to resolve. Our AI agents and human agents operate on a single platform with shared context, allowing Agentic AI to resolve issues, advance deals, and eliminate busywork through automation while seamlessly handing conversations to humans when needed, with full context preserved. Market-leading brands, including Randstad, Motorola Solutions, Netflix, the San Diego Padres, the Colorado Rockies Baseball Club, and Cal Athletics, trust Dialpad. Dialpad is backed by Andreessen Horowitz, GV, ICONIQ Capital, and T-Mobile. Being a Dialer At Dialpad, AI isn’t just a feature; it’s how our teams do their best work every day. We put powerful AI tools in every employee’s hands so they can move faster, think bigger, and achieve more. We believe every conversation matters. And we’ve built the platform that turns those conversations into insight and action, for our customers and ourselves. We look for people who are intensely curious and hold themselves to a high bar. Our ambition is significant, and achieving it requires a team that operates at the highest level. We seek individuals who embody our core traits: Scrappy, Curious, Optimistic, Persistent, and Empathetic . Your Role As a Sr. AI Engineer: Speech, you’ll be a senior technical leader on our Speech Team, shaping the models and systems that make Dialpad’s next-generation AI voice agents accurate, natural, responsive, and trustworthy. You’ll guide the team on state-of-the-art speech models, decoders, and evaluation approaches, while making hands-on contributions across speech recognition, enhancement, audio intelligence, and real-time inference. You’ll bridge ML science and production engineering: whether you are strongest in research, systems, or both, you’ll help turn advances in speech technology into reliable improvements for customers. This role offers broad ownership, meaningful technical influence, and the opportunity to mentor engineers while driving the next generation of Dialpad’s voice experience. This position reports to our Sr. Manager, AI Speech, and offers the opportunity to be based in our US or Canada Hub locations or work remotely. What You’ll Do Technical Leadership & Direction: Set technical direction for speech-model and decoder strategy across the team, guiding evaluation of state-of-the-art approaches and turning the strongest ideas into reliable improvements for our voice agents. Speech Model Development: Lead research, adaptation, and implementation of ASR/STT, speech-enhancement, and related audio models that improve recognition robustness, clarity, and performance in real-world calls. Decoders & Real-Time Pipeline: Improve the speech pipeline end to end, including decoding, endpointing, turn detection, streaming behavior, and the handoff between ASR, LLM, and TTS, with a focus on natural interactions and low latency. Research & Evaluation: Benchmark, prototype, fine-tune, distill, or otherwise adapt models and algorithms when doing so can create a meaningful advantage in voice-agent quality, latency, cost, or reliability. Production ML & Backend: Design and ship production-grade services and inference components for real-time speech, partnering with platform and backend engineers to make model improvements observable, scalable, and maintainable. Cross-Functional Leadership & Mentorship: Partner with speech, NLP, telephony, platform, product, and infrastructure engineers to shape the roadmap, lead technical reviews, mentor teammates, and translate speech advances into measurable gains for voice agents. Skills You’ll Bring Speech ML & Software Engineering: Strong Python programming skills and experience with deep learning frameworks such as PyTorch, plus the ability to work effectively in production codebases. Candidates may come from a research-heavy ML background, a backend/inference engineering background, or a combination of both. Speech & Audio Expertise: 5+ years of experience in speech ML, speech recognition, speech enhancement, audio AI, or a closely related field, with hands-on experience improving models or systems used in real-world applications. SOTA Models & Decoders: Deep understanding of modern ASR/STT architectures and decoding techniques, with the ability to evaluate, adapt, and explain trade-offs among accuracy, robustness, streaming behavior, latency, and compute cost. Research & Problem Solving: A track record of taking ideas from papers, experiments, or emerging m