Senior ML / AI Engineer

About the Role

Join a small, senior engineering team building the machine learning foundation for consumer software products. You will shape data pipelines, models, retrieval systems, and inference infrastructure that make AI-powered experiences useful and intuitive for everyday users.

What You'll Do

• Architect and build machine learning and retrieval systems for core product experiences.
• Design data pipelines that ingest, classify, enrich, and summarize large volumes of user data.
• Build scalable infrastructure for real-time and batch inference.
• Guide model selection, fine-tuning, embeddings, retrieval-augmented generation, and evaluation frameworks.
• Prototype product ideas and turn successful experiments into reliable systems.
• Partner with product, design, and engineering to deliver polished user-facing features.
• Establish strong practices for system quality, measurement, and failure analysis.

What We're Looking For

• At least 5 years of software or machine learning engineering experience, with a background in consumer AI or machine learning systems.
• Experience shipping machine learning features to real users, such as personalization, ranking, search, or recommendations.
• Experience developing custom models, including embeddings, recommendation, or personalization models, beyond prompt-based integrations alone.
• Strong experience with applied machine learning, LLMs, retrieval, classification, NLP, or related product systems.
• Familiarity with Python, FastAPI, PostgreSQL, vector databases, and embeddings.
• Experience with data pipelines, training and evaluation workflows, inference infrastructure, and end-to-end product development.
• A degree in computer science, mathematics, electrical engineering, or a related field, or comparable technical background.
• Comfort working in an early-stage or entrepreneurial environment and collaborating across product and design.

Compensation & Benefits

• Base salary: $200,000 to $300,000 annually
• Visa sponsorship: Available

Location

On-site in San Francisco, California, United States.