Senior Staff Machine Learning Engineer

Join Altana, a leading company in global trade technology. As a Senior Staff Machine Learning Engineer, you will lead the AI behind Altana Nexus, our agentic platform for global trade. You will define the architecture and roadmap for models and agentic systems, build reliable and cost-efficient systems for data ingestion and decision-making, and mentor senior engineers. You will also shape the product and the business by working with various teams to generate new business ideas and turn ambiguous problems into shipped capabilities.

- Conduire la direction technique des systèmes agentiques, définir l'architecture et la feuille de route des modèles et des systèmes agentiques. - Diriger la conception de systèmes fiables et rentables pour l'ingestion, la compréhension des documents, la résolution d'entités, l'inférence et le routage à l'échelle du commerce mondial. - Utiliser les retours des analystes, les résultats de production et les traces des agents pour affiner et post-entraîner les modèles, et maintenir chaque modèle en amélioration continue.

- Senior Staff-level technical leadership: you set architecture direction across teams, mentor engineers, and turn ambiguous problems into roadmaps - Hands-on experience building production LLM applications: retrieval-augmented generation (RAG), tool/function calling, structured outputs, and agentic workflows - Rigorous about evaluation: you've built eval suites, golden datasets and LLM-as-judge pipelines - You've shipped agentic systems in production and know their failure modes: tool use, planning, state, recovery and human-in-the-loop - You have strong written and verbal communication skills - Heavy user of AI coding tools (Cursor, Claude Code) in your daily workflow - 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 - Deep expertise in PyTorch and the modern Python ML stack (Hugging Face, scikit-learn, NumPy, Pandas/Polars) - BS/MS in Computer Science, Machine Learning, or a related field, or equivalent experience - 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 - Experience post-training or adapting LLMs (SFT, DPO, RLHF/RLAIF, reward modeling) for a production use case - 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 - You care deeply about engineering excellence, supportability and knowledge-sharing - Building multi-agent systems and agent tooling (e.g., LangGraph) - Vision-language models for document understanding (invoices, bills of lading, customs forms) - Hybrid retrieval: vector search, re-rankers, and embedding fine-tuning - 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)