ML Engineer

Tasks

• Design and own shared AI/ML components, frameworks, and pipelines (training, evaluation, and fine-tuning) across multiple product teams.
• Apply ML fundamentals and LLM techniques (prompting, fine-tuning, RAG) to solve real customer problems and evaluate performance in production.
• Prototype and build agent builder frameworks and embedded AI experiences, taking agentic AI from early exploration to production.
• Drive rapid prototyping to move from proof-of-concept to high-accuracy, performant systems.
• Architect and build full-stack, AI-native applications end-to-end, from backend services to production LLM integrations.

Requirements

• BS or higher in Computer Science or equivalent practical experience.
• 5+ years building production AI/ML systems (leadership experience is a big plus!).
• Strong CS fundamentals (data structures, algorithms, system design) + solid ML fundamentals (classification, regression, neural networks).
• Proficiency in Python and standard ML frameworks (PyTorch, TensorFlow, Pandas/NumPy).
• Hands-on experience with LLMs (prompt engineering, fine-tuning, LangChain).
• Experience building agentic systems, agent frameworks, or context/memory architectures.
• Familiarity with evaluation frameworks (online/offline) for measuring model and agent quality.
• Proficiency in one or more full-stack languages (JavaScript, Java) and scalable services (microservices, NoSQL/SQL, Kubernetes).

Schedule

• Onsite

How to apply

• Send your resume directly by email.

Location

• Oakland / Mountain View / San Diego, CA