Senior Staff AI/ML Research Engineer, Cloud AI Research

Google•Mountain View, CA

4h•$262,000 - $364,000

About The Position

Google is seeking a Senior Staff AI/ML Research Engineer for Cloud AI Research to help close the gap between frontier AI research and enterprise deployment. The organization operates at the intersection of foundational research, optimized ML infrastructure, and rapid prototyping, building AI agents and deploying them in enterprise settings. In this role, you will guide executive leadership, identify enterprise bottlenecks across Google Cloud, and architect blueprints for agent state machines. You will direct technical work on generalizable horizontal agents and vertical Forward Deployed Engineering deployments, aiming to create commercial and platform value while advancing AI science. The role also involves setting research and architectural direction, leading enterprise-facing engineering missions, and publishing research breakthroughs.

Requirements

Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, or equivalent practical experience.
At least 8 years of software development experience, including experience with Python, C++, Java, or JavaScript.
At least 8 years of experience leading large-scale ML system design and optimizing ML infrastructure, such as distributed training, model deployment, and evaluation.
Experience developing autonomous agents, multi-agent workflows, or agentic frameworks, such as AutoGen, CrewAI, LangGraph, ADK, tool-use/function-calling, or multi-agent systems.
Experience designing, pre-training, fine-tuning, or evaluating large language models and multimodal foundation models.

Nice To Haves

Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related technical discipline.
Extensive record of first-author scientific publication submissions on machine learning and NLP agents at venues such as NeurIPS, ICML, ICLR, or ACL.
Demonstrated success as a Senior Staff or Principal technical lead in enterprise-level SWAT, Pathfinding, or Forward Deployed Engineering environments.
Industry-leading expertise in reinforcement learning, reward modeling, and human/AI preference alignment techniques.
Deep mastery of test-time scaling methods, search-guided decoding, adversarial robustness, and complex alignment guardrails.

Responsibilities

Architect technical frameworks for high-velocity Strike Sprints, defining standards for intent-driven AI topologies, reflection loops, and agent state machines.
Serve as the principal technical anchor for Forward Deployed Engineering missions, working with VP- and Director-level partners to turn agentic prototypes into enterprise solutions.
Set architectural goals and lead development of generalizable horizontal agents, including examples such as AutoResearch and AutoFounder.
Direct research into agent architectures, novel planning frameworks, and self-improving foundation models.
Define centrally governed agentic playbooks across Google and publish research breakthroughs at machine learning conferences.
Guide executive leadership, deconstruct enterprise bottlenecks across Google Cloud, and architect blueprints for agent state machines.
Direct the technical agenda for horizontal agents and vertical Forward Deployed Engineering deployments.