Staff AI/ML Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Design and deliver production AI systems — including multi-agent orchestration, routing, and specialized agents that manage requests to achieve reliable results.

• Automate manual operational tasks across onboarding, support, exceptions, and document/data comprehension — transforming processes that typically take hours or days into mere seconds.

• Create the models that underpin decision-making — encompassing forecasting, prediction, matching/allocation, optimization, and reliability scoring, all grounded in data rather than assumptions, exposed as services accessible to the agent layer.

• Develop the learning loop. Implement mechanisms to record decisions and their outcomes, ensuring models improve continuously, supported by the necessary data and evaluation infrastructure.

• Take ownership of reliability and evaluation. Construct evaluation harnesses, tracing, observability, and guardrails for intricate AI workflows, where errors can lead to significant operational and financial repercussions — and validate that a model or agent outperforms the current standard before deployment.

• Make informed decisions on build versus rules — understanding when a model genuinely outperforms, when an agent is appropriate, and when a straightforward rule is the more sensible choice.

• Elevate team performance and foster growth — advance our prototyping-to-production pipeline while mentoring engineers as the AI team expands.

⛳️ Requirements

• You have successfully shipped production-level AI/ML solutions, not merely prototypes, and navigated the real trade-offs concerning edge cases, quality, latency, cost, and reliability.

• You possess substantial expertise in at least one of the following areas, with a working knowledge across both:

• - Generative/agentic AI — including multi-agent orchestration, tool/function calling, RAG, structured outputs, and the modern tech stack (e.g., LangGraph/LangChain, MCP), across various providers (Amazon Bedrock, Azure OpenAI, Anthropic, OpenAI).

• - Applied ML/decision intelligence — focusing on forecasting, optimization, matching/allocation, ranking, or predictive models that influence operational decisions with tangible business outcomes.

• You design and have confidence in your evaluation methods — both offline and online, linked to business results, incorporating safe rollout strategies (e.g., shadow mode) and drift monitoring.

• You are highly hands-on and capable of rapid deployment — proficient in Python, modern API/services (e.g., FastAPI), and possess a solid understanding of ML systems and architecture.

• You have experience building in operationally complex or high-stakes environments where quality and reliability are critical.

• You communicate effectively, make swift decisions, and can lead technical initiatives without relying heavily on established processes.

• Bonus points:

• - Experience in logistics, supply chain, transportation, marketplaces, mobility, or fulfillment.

• - Knowledge in operations research/optimization or reinforcement learning/bandits for sequential decision-making.

• - Familiarity with multimodal/document understanding, computer-use, or browser automation.

• - Expertise in real-time/streaming systems, feature stores, and large-scale production MLOps.

• - Patents or peer-reviewed publications, or experience as an early/founding engineer.

🏝️ Benefits

• Competitive salary, stock options, and performance-based bonuses

• Fully remote work environment

• Comprehensive medical, vision, and dental insurance