Senior Lead Applied AI Scientist

Job description

Design, build, and optimize AI solutions from concept through production deployment. Partner with business and product teams to identify opportunities, define success metrics, and validate value through rapid experimentation. Develop advanced AI systems leveraging machine learning, generative AI, retrieval, predictive modeling, and agentic architectures. Define evaluation frameworks and continuously improve quality, reliability, safety, performance, and cost.

Partner with Engineering to deliver scalable, production-ready solutions using MLOps and LLMOps best practices. Contribute reusable frameworks, evaluation assets, and technical standards that accelerate AI adoption across the enterprise. Provide technical leadership, mentorship, and guidance on complex AI initiatives. Job duties and responsibilities are subject to change based on evolving business needs and conditions. Seven plus years of experience in applied AI, machine learning, or data science, including production AI deployments.

Proven track record of delivering AI solutions that drive measurable business outcomes. Deep expertise in machine learning, statistics, experimentation, predictive analytics, and modern AI techniques. Hands-on experience building LLM, RAG, agentic, and machine learning solutions. Strong experience with AI evaluation, model performance optimization, responsible AI, and production monitoring. Proficiency in Python and modern AI/ML frameworks such as PyTorch, TensorFlow, Hugging Face, MLflow, or similar technologies.

Experience with MLOps, LLMOps, cloud AI platforms, APIs, and software engineering best practices. Strong product mindset, problem-solving skills, and ability to communicate complex concepts with technical and business stakeholders.

Preferred Qualifications

Master's degree or PhD in Computer Science, AI, Machine Learning, Statistics, or a related quantitative field. One plus years of experience building agent based solutions Experience operating enterprise-scale AI solutions in regulated or security-sensitive environments. Experience leading complex, cross-functional AI initiatives. Contributions to AI research, patents, publications, or open-source projects.