Research Engineer, Applied Research

Sierra’s Applied Research team advances the quality, speed, and cost efficiency of the models powering our agents across a wide range of tasks. Our work spans post-training open-weight models for specialized capabilities and pioneering new approaches to voice AI, turning research breakthroughs into reliable production systems.

WHAT YOU’LL DO

- Tackle unsolved applied AI and ML problems. Pushing the boundaries of post-training, voice AI, and long-horizon task execution, building agents that can reason, adapt, and reliably carry out complex tasks for customers.

- Determine when to build specialized models and when to use externally provided frontier intelligence, balancing quality, speed, and cost to deliver customer value.

- Turn ambiguous product and customer problems into well-framed machine learning problems.

- Develop, fine-tune, evaluate, and deploy models that improve Sierra’s customer-facing AI agents.

- Advance our post-training work, from supervised fine-tuning toward reinforcement learning and long-horizon optimization.

- Build rigorous evaluations that connect model performance to real-world agent quality.

- Work with large-scale, proprietary datasets spanning text and audio interactions.

- Collaborate across Sierra while taking ideas from experimentation through production deployment and customer impact.

WHAT YOU’LL BRING

- Strong experience building and deploying production machine learning and AI systems. We welcome backgrounds across applied ML, including search, ranking, recommendations, advertising, language, and speech.

- Excellent judgment in framing product problems as ML tasks and selecting the simplest & most effective approach.

- Experience working deeply with data, experimentation, evaluation, and model iteration.

- A practical, evidence-driven approach to ML, with strong judgement around when a problem calls for modeling and when a simpler solution will deliver the best outcome.

- The ability to operate with high agency and work across the stack when needed to deliver an outcome.

- Alignment with Sierra’s values, including Craftsmanship, Customer Obsession, and Competitive Intensity.

- A degree in computer science, machine learning, or a related field, or equivalent professional experience.

EVEN BETTER…

- Experience with supervised fine-tuning or reinforcement learning.

- Experience in search, ranking, recommendations, or advertising systems.

- Experience training and deploying language, speech, or multimodal models.

- Experience designing model evaluations tied to real-world product outcomes.

- Experience working with large-scale consumer datasets or high-volume ML products.

- Contributions to applied ML research or benchmarks.