Senior Staff Machine Learning Engineer

Altana•New York, NY

1d•$250,000 - $295,000•Hybrid

About The Position

Altana is hiring a Senior Staff Machine Learning Engineer to lead the AI behind Altana Nexus, its agentic platform for global trade. The role works with continuous streams of public and proprietary trade data—including shipments, customs filings, and trade documents—to build models and AI agents that support real-time risk, compliance, classification, and enforcement decisions for governments and large companies. The engineer will set technical direction for agentic systems and build reliable, cost-efficient pipelines from data ingestion and document understanding through entity resolution, inference, and model routing. They will adapt models using analyst feedback, production outcomes, and agent traces; build evaluation, tracing, and feedback systems; and help ensure models improve over time and regressions are caught in production. This is a senior technical leadership role involving mentorship, engineering standards, hiring and leveling practices, and cross-functional work with software engineers, data scientists, product managers, and customers to turn ambiguous problems into shipped capabilities. The position is based in Brooklyn, New York, with hybrid flexibility; candidates must live within commuting distance of the Williamsburg office. The listed annual base salary range is $250,000–$295,000 USD. Competitive equity grants are included in the majority of full-time offers, and the company offers either a discretionary bonus or variable compensation plan depending on the role. Benefits for full-time employees include flexible time off, paid parental leave, medical, vision and dental coverage, life and disability insurance, a 401(k) program, commuter benefits, a Calm subscription, pet insurance, an Employee Assistance Program, and a Dependent Care FSA.

Requirements

BS/MS in Computer Science, Machine Learning, or a related field, or equivalent experience.
10+ years building and shipping production ML systems, with a 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, including Hugging Face, scikit-learn, NumPy, and Pandas or Polars.
Hands-on experience building production LLM applications, including RAG, tool/function calling, structured outputs, and agentic workflows.
Experience shipping agentic systems in production and understanding their failure modes, including tool use, planning, state, recovery, and human-in-the-loop workflows.
Experience post-training or adapting LLMs for production, including SFT, DPO, RLHF/RLAIF, or reward modeling.
Experience building rigorous evaluation systems, such as evaluation suites, golden datasets, and LLM-as-judge pipelines.
Sound judgment about choosing frontier model APIs, fine-tuned open-weight models, or classical ML models while balancing cost, latency, and accuracy.
Senior Staff-level technical leadership, including setting architecture direction across teams, mentoring engineers, and turning ambiguous problems into roadmaps.
Passion for applying state-of-the-art techniques to real-world problems and willingness to work directly with data and domain details to achieve measurable outcomes.
Care for engineering excellence, supportability, and knowledge-sharing.
Strong written and verbal communication skills.
Daily use of AI coding tools such as Cursor or Claude Code.
Must be within commuting distance of Altana's Williamsburg, Brooklyn office.

Nice To Haves

Building multi-agent systems and agent tooling, such as LangGraph.
Experience with hybrid retrieval, including vector search, rerankers, and embedding fine-tuning.
Experience with vision-language models for document understanding, including invoices, bills of lading, and customs forms.
Experience with multilingual NLP.
LLMOps experience, including MLflow, Databricks Mosaic AI, and guardrails.
Experience with AI safety, guardrails, or auditability in regulated or high-stakes domains such as customs, legal, healthcare, or finance.

Responsibilities

Set the technical direction, architecture, and roadmap for agentic systems processing trade data and producing real-time risk, classification, and compliance decisions.
Lead the design of reliable, cost-efficient systems for ingestion, document understanding, entity resolution, inference, and routing across models at global-trade scale.
Use analyst feedback, production outcomes, and agent traces to fine-tune and post-train models, including SFT, DPO, and reinforcement learning with domain graders, where this measurably improves on prompting.
Design and build evaluations, tracing, observability, and feedback loops that guide releases and detect production regressions.
Mentor senior engineers, raise the technical bar across Engineering, and help shape ML hiring and leveling.
Work with software engineers, data scientists, product managers, and customers to identify business ideas and turn ambiguous problems into shipped capabilities.

Benefits

Flexible time off.
Paid parental leave: 14 weeks for non-birthing, adoptive, and foster parents, and up to 26 weeks for birthing parents, paid at 100% of base salary.
Medical, vision, and dental benefits with employer contributions; the high-deductible health plan is fully employer-paid for employees and includes an employer contribution to an HSA.
Flexible Spending Account option.
Life, short- and long-term disability, and AD&D insurance at no cost to employees.
Fidelity 401(k) retirement savings program.
Commuter benefits using pre-tax funds for public transit or parking.
Free premium Calm subscription.
Pet insurance and a pet veterinary service and telehealth discount plan.
Employee Assistance Program with confidential personal support.
Dependent Care FSA for childcare expenses.
Competitive equity grants included in the majority of full-time offers.
A discretionary bonus or variable compensation plan, depending on the role.