Applied Artificial Intelligence/ Machine Learning Lead - Vice President

What you'll do

• Develop agentic AI solutions and architectures, including workflow orchestration, memory, state, context, and fallback mechanisms.
• Build control-aware workflows, knowledge and retrieval layers, and specification-driven evaluation and regression systems.
• Improve agent quality through automated evaluation and feedback loops, and mentor AI/ML team members.

What they ask for

• PhD in a quantitative discipline or equivalent industry/research experience (including 3+ years with PhD-equivalent depth, or an MS with 5+ years).
• Demonstrated expertise building agentic AI systems, including several specified agent architecture and development practices.
• Hands-on experience with ML/DL methods and toolkits, such as PyTorch or TensorFlow, and the core Python data/ML stack.
• Experience designing business-outcome-aligned evaluation frameworks and scalable data/model workflows, with strong software engineering practices.

Nice to have

• Knowledge of search/ranking, reinforcement learning, or meta-learning; experience with knowledge graphs, entity resolution, or ontology design.
• Experience with A/B experimentation, metric-driven product development, CI pipelines, and unit/integration testing.

Pay

USD 171,000.00-$260,000.00 base salary

Tools

PyTorch, TensorFlow, Python, LLMs, RAG

AI focus

Designs and improves agentic AI systems, including LLM-based workflows, retrieval and knowledge-graph reasoning, reinforcement learning, automated evaluation, and self-improvement.