Machine Learning Lead (LLM)

Descrição da Vaga

Requisitos

• 1+ years leading data science teams; 6+ years in ML or data engineering
• Strong background in applied statistics, model selection, tuning, and evaluation
• Proficient in Python, SQL, and modern ML frameworks (PyTorch, TensorFlow, or JAX)
• Experienced in building and deploying production ML and deep learning pipelines
• Familiar with LLMs, embeddings, agentic workflows, and RAG systems
• Comfortable with cloud and DevOps tools (Docker, Kubernetes, Terraform)
• Skilled in exploratory data analysis and handling imperfect real-world data
• You’ll thrive in a fast-moving environment where priorities evolve quickly and impact is immediate
• Collaborative leader who communicates clearly with technical and nontechnical teams
• Eligibility: Candidates must be authorized to work in the U.S

Responsabilidades

• Reporting to the Director of Engineering, you’ll be in charge of the roadmap and technical direction
• You'll be collaborating with the team to build the infrastructure, train the models, and deploy them to production
• If you’re motivated to use your technical expertise for meaningful, mission-driven work that advances the public good, this role offers the chance to make a tangible impact
• Lead a team of senior data scientists focused on fine-tuning large language models, conducting cutting-edge R&D, and building production inference systems
• Collaborate with senior leadership to define the team roadmap and align priorities with organizational goals
• Lead weekly meetings and standups, keeping the team unblocked and execution moving forward
• Provide technical direction across projects using open-weight and off-the-shelf LLMs, as well as other advanced ML techniques
• Oversee experimentation, optimization, and data quality to ensure models are accurate, reliable, and production-ready
• Foster creative problem-solving and methodological rigor when challenges require custom solutions beyond standard ML approaches
• Translate complex model outputs into actionable insights for stakeholders, ensuring technical work drives real-world impact

Benefícios