AI Machine Learning Scientist

What you'll do

• Design, develop, and deploy Generative AI solutions including LLMs, RAG pipelines, and agentic workflows at enterprise scale.
• Build infrastructure and data pipelines to connect structured and unstructured sources for AI-driven applications.
• Create evaluation frameworks and automated testing strategies to measure model quality, accuracy, bias, and safety.
• Establish monitoring, observability, and governance processes to ensure production systems remain reliable and compliant.
• Translate complex business requirements into production-ready AI capabilities in collaboration with engineering and product teams.
• Optimize AI systems for scalability, latency, reliability, and cost efficiency.
• Implement Responsible AI practices including audit-ready documentation and model governance controls.
• Conduct experimentation, benchmarking, and model comparison activities to drive innovation and informed decision-making.

What we're looking for

• Bachelor’s degree in a highly quantitative field or equivalent combination of education and experience.
• 4 or more years of experience in machine learning, data modeling, or configuration management.
• Experience building and deploying LLM-based applications in production environments (preferred).
• Experience with RAG systems, vector databases, and prompt engineering techniques (preferred).
• Experience with MLOps practices including CI/CD, model monitoring, and lifecycle management (preferred).
• Proficiency with Python and frameworks like PyTorch, TensorFlow, LangChain, or Hugging Face (preferred).
• Familiarity with Responsible AI principles, governance, and bias testing (preferred).
• Experience in healthcare or other regulated industries (preferred).