About You

You’re an exceptional builder who thrives on responsibility and impact, with a track record of thoughtful and pragmatic decision-making. You’ve solved complex ML problems such as ranking, recommendation, or NER in commercial or consumer products, and you excel at collaborating to tackle tough challenges with minimal supervision. Just as importantly, you want to be part of a team you genuinely enjoy working with.

Responsibilities

• Build ML and product infrastructure powering high-impact products.
• Drive dataset strategy, inference systems, and domain logic to improve accuracy and coverage at scale.
• Apply cutting-edge LLMs to create robust and flexible document understanding systems within broader ML pipelines.
• Perform deep error analysis and engineer scalable solutions for diverse real-world data.
• Work directly with end users to understand needs and build products they love.
• Integrate inference pipelines into complete, production-grade products.
• Operate with autonomy and judgment, balancing technical and market constraints to deliver value.
• Encode institutional domain expertise into scalable expert systems.

Requirements

• 5+ years of experience working with commercial ML systems with meaningful ownership of design and outcomes.
• Strong fundamentals in building, measuring, and iterating on ML systems for enterprise or consumer products.
• Proficiency in Python and ML libraries (pandas, scikit-learn, spaCy, PyTorch, TensorFlow, Keras).
• Experience with cloud providers (AWS, GCP), containers (Docker, Kubernetes), web development (Flask, Django), and data/storage systems (Postgres, SQL, S3/GCS).
• Interest or experience in LLM prompt engineering.
• Willingness to work full-time, on-site in San Francisco.