O
Applied AI Engineer
OSI Engineering, Inc.
5 hours ago
Full-time
On-site
Cupertino, California, United States
Applied AI Engineer (ML + Agentic Development) for an Engineering Team with a Global Consumer Electronics Company in Cupertino, CA
Summary: An engineering team in Cupertino is looking for an Applied AI Engineer to build and improve internal AI agents and the web tools that show their results. About half of the role is agent development and half is full-stack work. You'll work alongside ML engineers and wireless/cellular engineers to turn their needs into working tools. All of the work is on internal engineering tools; nothing is customer-facing.
Responsibilities:
Maintain and extend internal AI agents in a multi-agent environment: add context, build new features and improve how agents connect and hand off work
Build web portals and dashboards (React or Angular) that display agent outputs to engineering users
Develop and maintain the backend services and APIs behind those agents and portals
Apply existing ML models to engineering data using Python (PyTorch, NumPy, Pandas, scikit-learn)
Turn requirements from ML and cellular engineers into technical designs and working features
Write and run unit tests so new features don't break existing functionality
Key Qualifications:
3–5 years of hands-on experience applying ML models in production or internal tools. The focus is using and integrating existing models, not researching new ones.
6–12 months of hands-on agent development, including multi-agent systems and how agents connect through tools, MCP servers and skills
Full-stack experience: backend/API development plus a modern front-end framework (React or Angular)
Strong Python, including PyTorch, NumPy, Pandas and scikit-learn
Experience with AI coding tools such as Claude Code or Codex
Nice to Have: Experience with multi-agent frameworks such as LangGraph or AutoGen
Knowledge of the cellular or wireless domain (LTE/5G)
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Summary: An engineering team in Cupertino is looking for an Applied AI Engineer to build and improve internal AI agents and the web tools that show their results. About half of the role is agent development and half is full-stack work. You'll work alongside ML engineers and wireless/cellular engineers to turn their needs into working tools. All of the work is on internal engineering tools; nothing is customer-facing.
Responsibilities:
Maintain and extend internal AI agents in a multi-agent environment: add context, build new features and improve how agents connect and hand off work
Build web portals and dashboards (React or Angular) that display agent outputs to engineering users
Develop and maintain the backend services and APIs behind those agents and portals
Apply existing ML models to engineering data using Python (PyTorch, NumPy, Pandas, scikit-learn)
Turn requirements from ML and cellular engineers into technical designs and working features
Write and run unit tests so new features don't break existing functionality
Key Qualifications:
3–5 years of hands-on experience applying ML models in production or internal tools. The focus is using and integrating existing models, not researching new ones.
6–12 months of hands-on agent development, including multi-agent systems and how agents connect through tools, MCP servers and skills
Full-stack experience: backend/API development plus a modern front-end framework (React or Angular)
Strong Python, including PyTorch, NumPy, Pandas and scikit-learn
Experience with AI coding tools such as Claude Code or Codex
Nice to Have: Experience with multi-agent frameworks such as LangGraph or AutoGen
Knowledge of the cellular or wireless domain (LTE/5G)
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