Machine Learning Lead (LLM)

Blue Rose Research builds data and AI tools that help Democrats win elections. Our team combines engineering, data science, and political strategy to power decisions for the country’s top campaigns and progressive organizations. We forecast elections, test ads, and use generative AI to help campaigns understand what’s happening in the news; then respond fast with messages that actually work. We have guided how hundreds of millions of dollars are spent in modern campaigns. We’re a small, mission-driven team that builds fast, experiments boldly, and helps progressives communicate and win—guided by curiosity, purpose, and a genuine desire to use technology for good.

We’re looking for a Machine Learning Lead for a small team of senior data scientists who are developing ML-driven products that power data-informed strategy for civic leaders and organizations. Reporting to the Director of Engineering, you’ll be in charge of the roadmap and technical direction. This is a hands-on role. 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

• 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.