3 hours ago
Base Salary
$205k - $240k/yr
Responsibilities
- Define the architecture, roadmap, and technical direction for agentic systems processing global trade data in real time.
- Lead reliable and cost-efficient pipelines for ingestion, document understanding, entity resolution, inference, and model routing.
- Fine-tune and post-train models using SFT, DPO, and reinforcement learning with domain graders when appropriate.
- Build evaluation suites, tracing, observability, golden datasets, and feedback loops to detect production regressions and improve models.
- Mentor senior engineers, raise the technical bar, and help shape ML hiring and leveling.
- Collaborate with software engineers, data scientists, product managers, and customers to turn ambiguous problems into shipped capabilities and new business opportunities.
Requirements
- BS/MS in Computer Science, Machine Learning, or a related field, or equivalent experience.
- 8+ years building and shipping production ML systems and 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/Polars.
- Hands-on experience building production LLM applications using RAG, tool or function calling, structured outputs, and agentic workflows.
- Production experience with agentic systems, including tool use, planning, state management, recovery, and human-in-the-loop workflows.
- Experience adapting or post-training LLMs through SFT, DPO, RLHF/RLAIF, or reward modeling.
- Experience building evaluation suites, golden datasets, and LLM-as-judge pipelines.
- Ability to select among frontier model APIs, fine-tuned open-weight models, and classical ML models while balancing cost, latency, and accuracy.
- Strong written and verbal communication, engineering judgment, supportability practices, and knowledge-sharing orientation.
- Heavy daily use of AI coding tools such as Cursor and Claude Code.
- Preferred experience includes multi-agent systems and LangGraph, hybrid retrieval, vector search, re-rankers, embedding fine-tuning, vision-language models, multilingual NLP, MLflow, Databricks Mosaic AI, guardrails, and AI safety or auditability in regulated or high-stakes domains.
Benefits
- Remote or hybrid work in the United States or UK, with hub options in New York City, Boston, Washington D.C., or London.
- Flexible Time Off policy.
- Paid parental leave of 14 weeks for non-birthing, adoptive, and foster parents and up to 26 weeks for birthing parents at 100% of base salary.
- Medical, vision, and dental benefits with employer contributions, including an employer-paid high deductible health plan and HSA contribution, plus an FSA option.
- Employer-paid life, short-term disability, long-term disability, and AD&D insurance.
- Fidelity 401(k) savings program.
- Pre-tax commuter benefits for public transit or parking.
- Free premium Calm subscription, pet insurance and veterinary telehealth discounts, Employee Assistance Program, and Dependent Care FSA.
Tech Stack
Apache SparkAWSAzureDatabricksDockerGitKubernetesMLflowNumPyPandasPostgreSQLPythonPyTorchscikit-learn
Categories
About Altana
Altana builds an AI-powered network and software platform for global trade visibility and value chain management used by enterprises and governments. Its SaaS products connect importers, suppliers, logistics providers, and customs agencies to share data for compliance, classification, and supply chain risk. Founded in 2018 and headquartered in New York, Altana serves customers such as Maersk, Boston Scientific, L.L.Bean, U.S. Customs and Border Protection, and the UK Department for Business and Trade.