[Remote] Staff AI/ML Engineer

Note: The job is a remote job and is open to candidates in USA. Burq is a company focused on simplifying the delivery process through innovative AI solutions. They are seeking a Staff AI/ML Engineer to build core AI systems that automate logistics operations and improve decision-making through advanced models.

Responsibilities

• 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

Skills

• 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
• 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

Benefits

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

Company Overview