Senior Staff Machine Learning Engineer

We're looking for a Senior Staff Machine Learning Engineer to lead the AI behind Altana Nexus, our agentic platform for global trade. You'll work on a continuous stream of public and proprietary trade data (shipments, customs filings, trade documents), and build the models and AI agents that turn it into real-time decisions on risk, compliance and enforcement for governments and the world's largest companies.

Your Responsibilities

Drive the technical direction for agentic systems. Define the architecture and roadmap for the models and agentic systems that process trade data as it arrives (shipments, customs declarations, invoices, bills of lading) and turn it into risk, classification and compliance decisions in real time.

Build the pipeline from ingestion to decision. Lead the design of reliable, cost-efficient systems for ingestion, document understanding, entity resolution, inference and routing across models, at the scale of global trade.

Adapt models to trade. Use analyst feedback, production outcomes and agent traces to fine-tune and post-train models (SFT, DPO, RL with domain graders) where it measurably beats prompting, and keep every model improving over time.

Design the observability and feedback stack. Build the evals, tracing and feedback loops that decide what ships and catch regressions in production.

Lead beyond your team. Mentor senior engineers, raise the technical bar across Engineering, and help shape how we hire and level ML talent.

Shape the product and the business. Work with software engineers, data scientists, product managers and customers to generate new business ideas and turn ambiguous problems into shipped capabilities.

About You

BS/MS in Computer Science, Machine Learning, or a related field, or equivalent experience

10+ years building and shipping ML systems in production, with a proven track record of delivering product-oriented ML solutions, including recent work on LLM-powered products

Deep expertise in PyTorch and the modern Python ML stack (Hugging Face, scikit-learn, NumPy, Pandas/Polars)

Hands-on experience building production LLM applications: retrieval-augmented generation (RAG), tool/function calling, structured outputs, and agentic workflows

You've shipped agentic systems in production and know their failure modes: tool use, planning, state, recovery and human-in-the-loop

Experience post-training or adapting LLMs (SFT, DPO, RLHF/RLAIF, reward modeling) for a production use case

Rigorous about evaluation: you've built eval suites, golden datasets and LLM-as-judge pipelines

Sound judgment on when to use a frontier model API, a fine-tuned open-weight model, or a classical ML model, balancing cost, latency, and accuracy

Senior Staff-level technical leadership: you set architecture direction across teams, mentor engineers, and turn ambiguous problems into roadmaps

Passionate about applying SOTA techniques to real-world problems, with a willingness to get your hands dirty in the data and domain to achieve measurable outcomes

You care deeply about engineering excellence, supportability and knowledge-sharing

You have strong written and verbal communication skills

Heavy user of AI coding tools (Cursor, Claude Code) in your daily workflow

Nice to have, but not required

Building multi-agent systems and agent tooling (e.g., LangGraph)

Hybrid retrieval: vector search, re-rankers, and embedding fine-tuning

Vision-language models for document understanding (invoices, bills of lading, customs forms)

Multilingual NLP

LLMOps: MLflow, Databricks Mosaic AI, and guardrails

Experience with safety, guardrails or auditability for AI in regulated or high-stakes domains (e.g., customs, legal, healthcare, finance)

Technologies we love

Languages: Python, Spark

Tools: Docker, Git, Kubernetes, Swagger/OpenAPI, AWS, Azure

Datastores: Databricks, OpenSearch, Postgres

ML Tools: PyTorch, Hugging Face, FAISS, MLflow

LLM Tools: vLLM, LangGraph, LangSmith/Braintrust, frontier model APIs

This role is based in Brooklyn, NY, USA with hybrid work flexibility and candidates must be within commuting distance from our Williamsburg, Brooklyn office.

US Salary Range and Benefits

$250,000 - $295,000 USD