Staff ML Product Engineer

Key Responsibilities

• Own delivery of ML-powered features from concept through production. You are responsible for the feature working in practice.

• Ensure models, retrieval systems, and agent workflows function correctly together across the full system.

• Lead implementation of ML-driven features, coordinating with ML engineers and the rest of the team to get features shipped.

• Build and maintain evaluation systems, including datasets, scoring approaches, and repeatable testing to detect regressions.

• Design and iterate on prompts and agent instructions to ensure correct and predictable system behavior.

• Establish and improve observability, debugging, and testing practices for ML systems.

• Improve the structure, reliability, and maintainability of the ML codebase while preserving development speed.

• Work primarily in Python, and contribute in Go and other languages where needed.

• Modify and work with pipelines, retrieval systems, and model behavior when required.

• Orchestrate workflows across APIs, external systems, and multiple data sources.

• Balance rapid experimentation with longer-term system quality.

• Work with customers and internal stakeholders to ensure solutions align with real-world usage.

Experience

• Strong software engineering background, with experience building and owning production systems end to end.

• Strong proficiency in Python, with a track record of building well-structured and maintainable systems.

• Experience delivering complex features in production environments, ideally involving ML or AI systems.

• Demonstrated ability to take ownership of ambiguous problems and drive them to working solutions.

• Experience working with LLMs, RAG systems, or agent-based workflows.

• Experience integrating multiple systems, APIs, and data sources into cohesive product functionality.

• Experience designing or working with evaluation systems for ML quality.

• Experience debugging production systems, including handling edge cases and failure modes.

• Experience with observability and debugging in ML or backend systems.

• Experience working with pipelines, retrieval systems, or model behavior such as ranking, fine-tuning, or prompt tuning.

• Comfortable operating in fast-moving environments with high ownership.

• Familiarity with Go and ability to work in a multi-language backend environment.

• Experience working with customers or customer-facing systems, incorporating feedback into what gets built.

• Familiarity with frontend or full-stack development.

• Experience with MLOps systems, data pipelines, or production ML infrastructure.

• Familiarity with open source models such as LLaMA, Qwen, DeepSeek, Kimi, or similar.

Human Skills

• Ownership mindset with a focus on delivering working systems in production.

• Strong product judgment, with an understanding of how system behavior impacts user experience and trust.

• Bias toward action, with a focus on learning through building and iteration.

• Ability to operate effectively in ambiguous environments.

• Systems thinking, including attention to correctness and failure modes.

• Curiosity about how systems behave in practice and how customers use them.

• Low ego, with a focus on team outcomes.

What We Offer

• Early-Stage Ownership: Join at the ground floor of a company with real traction and momentum.

• Empowered Culture: We value autonomy, candor, and craft. You'll be trusted to lead.

• Cutting-Edge Tech: Work with the latest in AI, backend systems, and intelligent infrastructure.

• Meaningful Impact: Shape a platform that transforms how organizations activate knowledge.

• Holistic Benefits: Competitive comp, equity, 100% paid healthcare, 401K, flexible PTO, and a team that truly cares.