Senior Staff AI/ML Engineer - Cloud AI Research (Equity)

Google LLC; Mountain View (CA); On-site; USD 262,000 - 364,000; Full time

Job summary

Google Mountain View seeks a senior software engineer leading ML systems for agentic AI, bridging research and production at scale. You will shape architectures for high-velocity agent state machines and enterprise deployments.

You will collaborate with executives, guide FDE programs, define horizontal agents, publish breakthroughs, and help Google's AI native pathfinding efforts. The role requires in-person interviews in many cases and deep ML/NLP expertise.

Qualifications

• Bachelor's degree in CS/AI/ML or equivalent practical experience.
• 8+ years leading large-scale ML system design and ML infrastructure optimization.
• Experience developing autonomous agents, multi-agent workflows, or agentic frameworks.
• Experience designing, pre-training, fine-tuning, or evaluating LLMs and multimodal models.

Responsibilities

• Guide executive leadership and deconstruct enterprise bottlenecks across Google Cloud.
• Architect blueprints for agent state machines and generalizable horizontal agents.
• Lead Forward Deployed Engineering deployments and translate prototypes into enterprise solutions.
• Set architectural goals for agent frameworks and self-improving models.
• Publish breakthroughs at ML conferences and define centralized agentic playbooks.

Skills

Large-scale ML systems

Distributed training

Autonomous agents / multi-agent

LLMs / multimodal models

Agentic frameworks

Tool-use / function-calling

Education

Bachelor's degree in CS / AI / ML or equivalent

Tools

AutoGen

CrewAI

LangGraph

ADK

Job description

Google Mountain View seeks a senior software engineer leading ML systems for agentic AI, bridging research and production at scale. You will shape architectures for high-velocity agent state machines and enterprise deployments.

You will collaborate with executives, guide FDE programs, define horizontal agents, publish breakthroughs, and help Google's AI native pathfinding efforts. The role requires in-person interviews in many cases and deep ML/NLP expertise.