Staff AI/ML Engineer

Role Overview

• Design and ship production AI systems — multi-agent orchestration, routing, and specialized agents that take a request and carry it through to a reliable outcome.
• Automate manual operational work across onboarding, support, exceptions, and document/data understanding — turning processes that take hours or days into seconds.
• Build the models behind the decisions — forecasting, prediction, matching/allocation, optimization, and reliability scoring that ground the product in data instead of guesswork, exposed as services the agent layer can call.
• Design the learning loop. Instrument decisions and their outcomes so models continuously improve, with the data and evaluation infrastructure to support it.
• Own reliability and evaluation. Build the eval harnesses, tracing, observability, and guardrails for complex AI workflows where mistakes carry real operational and financial consequences — and prove a model or agent beats the status quo before it ships.
• Make the build-vs-rules calls — know when a model genuinely wins, when an agent is the right tool, and when a simple rule is the smarter answer.
• Raise the bar and help the team grow — push our prototyping-to-production pipeline forward and mentor engineers as the AI team scales.

Requirements

• You've shipped production AI/ML, not just prototypes — and dealt with the real tradeoffs of edge cases, quality, latency, cost, and reliability.
• You have real depth on at least one of these, and working fluency across both:
• Generative / agentic AI — multi-agent orchestration, tool/function calling, RAG, structured outputs, and the modern stack (e.g., LangGraph/LangChain, MCP), across providers (Amazon Bedrock, Azure OpenAI, Anthropic, OpenAI).
• Applied ML / decision intelligence — forecasting, optimization, matching/allocation, ranking, or prediction models that drive operational decisions with measurable business impact.
• You design and trust your own evaluation — offline and online, tied to business outcomes, with safe rollout (e.g., shadow mode) and drift monitoring.
• You're deeply hands-on and ship fast — strong in Python, modern API/services (e.g., FastAPI), and sound ML-systems and architecture instincts.
• You've built for operationally complex or high-stakes environments where quality and reliability genuinely matter.
• You communicate clearly, make decisions quickly, and can lead technical work without needing heavy process.
• Bonus points:
• Background in logistics, supply chain, transportation, marketplaces, mobility, or fulfillment.
• Operations research / optimization, or reinforcement learning / bandits for sequential decision-making.
• Multimodal / document understanding, computer-use, or browser automation.
• Real-time / streaming systems, feature stores, and production MLOps at scale.
• Patents or peer-reviewed publications, or experience as an early/founding engineer.

Tech Stack

• Azure
• Python

Benefits

• Competitive salary, stock options, and performance-based bonuses
• Fully remote
• Comprehensive medical, vision, and dental insurance