Research Engineer, Applied Research

About us

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.