Senior Staff Machine Learning Engineer

Altana•Brooklyn, NY

23h•Hybrid

About The Position

Altana is seeking a Senior Staff Machine Learning Engineer to lead the AI behind Altana Nexus, its agentic platform for global trade. The role works with a continuous stream 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 position is based in Brooklyn, New York, with hybrid work flexibility; candidates must live within commuting distance of the Williamsburg office. The engineer will set technical direction for agentic systems, lead architecture and roadmaps, and build reliable, cost-efficient pipelines spanning data ingestion, document understanding, entity resolution, inference, and model routing. They will adapt and improve models using analyst feedback, production outcomes, and agent traces; build evaluation, tracing, and feedback systems; and help ensure production quality. The role also includes mentoring senior engineers, raising engineering standards, shaping hiring and leveling practices, and working across engineering, data science, product, and customer teams to turn ambiguous problems into shipped capabilities. Altana offers a stated annual base salary range of $250,000–$295,000, competitive equity grants in most full-time offers, and either a discretionary bonus or variable compensation depending on the role. Benefits include flexible time off; paid parental leave; medical, dental, and vision coverage; life, disability, and AD&D insurance; a 401(k) savings program; commuter benefits; access to Calm; pet insurance; an Employee Assistance Program; and a Dependent Care FSA.

Requirements

Bachelor’s or master’s degree 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 LLM-powered product work.
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 retrieval-augmented generation, tool or function calling, structured outputs, and agentic workflows.
Production experience shipping agentic systems 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 use cases, including SFT, DPO, RLHF/RLAIF, or reward modeling.
Experience building evaluation suites, golden datasets, and LLM-as-judge pipelines.
Sound judgment in choosing between frontier model APIs, fine-tuned open-weight models, and 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 current techniques to real-world problems, including willingness to work directly with data and domain details to achieve measurable outcomes.
Commitment to 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

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

Responsibilities

Set technical direction and define the architecture and roadmap for agentic systems that process trade data and produce 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, and continually improve deployed models.
Design and build evaluation, tracing, and feedback systems that guide releases and detect production regressions.
Mentor senior engineers, raise the technical bar across Engineering, and help shape ML hiring and leveling.
Collaborate with software engineers, data scientists, product managers, and customers to develop business ideas and turn ambiguous problems into shipped capabilities.

Benefits

Flexible Time Off policy.
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 for public transit or parking.
Free premium Calm subscription.
Pet insurance and access to a pet veterinary service and telehealth discount plan.
Employee Assistance Program with confidential personal support.
Dependent Care FSA.
Competitive equity grants are included in the majority of full-time offers.
Discretionary bonus or variable compensation, depending on the role.