Staff AI/ML Engineer

Design, build, and deploy production-grade AI systems that combine multi-agent orchestration, decision intelligence, and automation to replace and enhance complex operational workflows.

• Develop agentic AI systems capable of end-to-end task execution, including routing, tool use, and workflow automation across operational domains such as support, onboarding, and exceptions handling.
• Build applied machine learning models for forecasting, prediction, matching, ranking, and optimization that directly inform product and business decisions.
• Design and implement continuous learning systems, including data pipelines, feedback loops, and evaluation frameworks to improve model performance over time.
• Own AI system reliability through robust evaluation frameworks, observability, tracing, guardrails, and safe deployment practices such as shadow testing.
• Define when to use models, agents, or rule-based systems, making pragmatic build-vs-buy and build-vs-rule decisions.
• Collaborate closely with product and engineering teams to bring AI prototypes into scalable, production-ready systems.
• Mentor engineers and contribute to raising the technical bar across AI development and system design practices.

Requirements:

This role requires a highly hands-on AI/ML engineer with proven experience building and scaling real-world AI systems in production environments.

• Demonstrated experience shipping production AI/ML systems, not just prototypes, with attention to latency, cost, reliability, and edge cases.
• Strong expertise in either generative/agentic AI systems (multi-agent workflows, tool use, RAG, structured outputs, orchestration frameworks like LangGraph or LangChain) or applied machine learning for decision intelligence (forecasting, ranking, optimization, matching).
• Solid Python engineering skills and experience building production APIs and services (e.g., FastAPI) in modern distributed systems.
• Experience designing evaluation frameworks, including offline/online testing, A/B testing, drift detection, and safe rollout strategies.
• Strong understanding of ML system design, including data pipelines, feature engineering, and production monitoring.
• Ability to operate in high-stakes, operational environments where system reliability directly impacts business outcomes.
• Strong communication skills and ability to lead technical initiatives with autonomy and clarity.
• Bonus: Experience in logistics, marketplaces, optimization/operations research, real-time systems, or agent-based automation.
• Bonus: Exposure to reinforcement learning, bandits, multimodal systems, or large-scale MLOps platforms.

Benefits:

• Competitive compensation including salary, equity, and performance-based bonuses.
• Fully remote work environment with flexibility across the United States and Canada.
• Comprehensive medical, dental, and vision insurance coverage.
• Equity participation in a high-growth, venture-backed organization.
• Opportunity to work on cutting-edge AI systems with real-world operational impact.
• Regular offsites and opportunities for in-person collaboration.
• Fast-paced, high-ownership culture focused on shipping, learning, and continuous improvement.