Research Engineer, Applied Research

Sierra • San Francisco, CA

1d • Onsite

About The Position

Sierra is the leading platform for customer-facing AI agents, working with many of the world's biggest brands to transform how they serve customers and grow their businesses. We are primarily an in-person company based in San Francisco, with growing offices across North America, Europe, and Asia. Our co-founders are Bret Taylor and Clay Bavor. Bret currently serves as Board Chair of OpenAI. Previously, he was co-CEO of Salesforce (which had acquired the company he founded, Quip) and CTO of Facebook. Bret was also one of Google's earliest product managers and co-creator of Google Maps. Before founding Sierra, Clay spent 18 years at Google, where he most recently led Google Labs. Earlier, he started and led Google’s AR/VR effort, Project Starline, and Google Lens. Before that, Clay led the product and design teams for Google Workspace. 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.

Requirements

• 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.

Nice To Haves

• 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.

Responsibilities

• 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.

Benefits

• Flexible (unlimited) paid time off
• Medical, dental, and vision benefits for you and your family
• Life insurance and disability benefits
• Retirement plan dependent on country of employment
• Parental leave
• Fertility and family building benefits through Carrot
• Lunch, as well as delicious snacks and coffee to keep you energized
• Discretionary benefit stipend giving people the ability to spend where it matters most
• Free alphorn lessons

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Associate degree