Lead AI Engineer / Data Scientist || Need Local to CA.

About the Role

You will design and build production AI systems end to end across multiple domains: Generative and Agentic AI (including working with foundation models such as Claude), Computer Vision on unstructured data, forecasting, and optimization. Your work spans understanding the customer's problem and datasets, selecting the right algorithms, fine-tuning, and deploying models, architecting agentic workflows, and standing up the surrounding infrastructure. You will be the technical face of these solutions: guiding developers, resolving customer issues in real time, and translating ambiguous requirements into concrete, workable plans.

The ideal candidate has a strong track record of working with roughly 10+ AI/ML projects deployed to production and is as comfortable writing production deep learning code as they are sitting in front of a customer diagnosing an issue and proposing a path forward.

Key Responsibilities

• Design end-to-end ML/LLM and agentic solutions, from problem framing and data strategy through to deployment and monitoring.
• Architect agentic systems: multi-step, tool-using, and multi-agent workflows: including orchestration, tool/function integration, memory, and guardrails.
• Own the technical architecture for solutions: model selection, fine-tuning approach, agent/orchestration design, serving strategy, API design, and infrastructure footprint.
• Lead and mentor a team of data scientists and developers, break complex, ambiguous customer requirements into structured project plans with clear milestones and deliverables.

• Apply strong algorithmic fundamentals to select, adapt, and implement the right approach for each problem: classic ML, deep learning, or generative/agentic AI.
• Build deep learning models on unstructured data (images, video, text, audio, sensor/time-series) for real-world production use.
• Design and ship computer vision solutions (detection, classification, segmentation, OCR, tracking, etc.) at production quality and scale.
• Develop forecasting models (time-series and demand/behavioral forecasting) and integrate them into decisioning workflows.
• Work with foundation models including Claude and other LLMs: prompting, fine-tuning, evaluation, and integration.

Required Qualifications:

• Bachelor's & Master's degree in Computer Science, Data Science, Machine Learning, or a related field (or equivalent practical experience).
• Experience in agentic frameworks and protocols (e.g., LangGraph, LlamaIndex, AutoGen, CrewAI, MCP) and with RAG and tool-use patterns.
• Familiarity with MLOps tooling (experiment tracking, CI/CD for ML, model registries, monitoring).
• Experience with distributed training and inference optimization (quantization, batching, GPU utilization).
• Exposure to containerization and orchestration (Docker, Kubernetes).

Technical Frameworks & Toolkit:

Agentic AI frameworks & protocols: Claude Agent SDK, Anthropic / OpenAI SDKs, LangGraph, AutoGen, CrewAI, Semantic Kernel, and the