Snapshot

We are working on bringing capabilities and experiences from both 1P Google Services (e.g. Maps, Youtube, Gmail, Calendar, etc.) as well as 3P services into Gemini – all in service of making Gemini the best LLM-supercharged universal assistant there is. Our team of full stack Machine Learning Engineers are responsible for improving the Tool Use platform, and horizontal model quality for all services that would like to integrate with GeminiApp, and building new agentic experiences powered by them.

About Us

Artificial Intelligence could be one of humanity’s most useful inventions. At Google DeepMind, we’re a team of scientists, engineers, machine learning experts and more, working together to advance the state of the art in artificial intelligence. We use our technologies for widespread public benefit and scientific discovery, and collaborate with others on critical challenges, ensuring safety and ethics are the highest priority.

The Role

In this role, you will work on bringing conversational, multimodal agentic experiences powered by 1P and 3P tools into Gemini and Gemini Live. This team focuses on horizontal model quality, and infrastructure for scaling to all APIs/MCPs out in the world. We are looking for highly skilled Applied ML software engineers with LLM expertise. You should have experience building products based around AI models and slotting new capabilities into an end-to-end production stack.

This is a fast-paced role with aggressive deadlines, where you should be prepared to wear many hats and be ready to solve a wide range of exciting technical problems. Some of the things we are working on:

Improving the model’s ability to reason through complex requests, call various tools to fulfill the user request, including complex scenarios like chaining multiple tools across multiple turns.
Building new agentic experiences powered by our core tools with multi-modal input in GeminiLive with camera and screenshare.
Identifying gaps based on user feedback, and improving the model’s capability for function calling.
Building data collection and eval infra to collect eval data in scalably and autoraters, autousers, automatic prompt optimization to help scale hill-climb and push the frontiers of what Gemini can do with MCP integrations.

About You

We seek out individuals who thrive in ambiguity and have a shipping mindset, willing to help out with whatever moves prototypes forward. We regularly need to invent novel solutions to problems, and often change course if our ideas don’t work out, so flexibility and adaptability to work on any project is a must.

In order to set you up for success as a Machine Learning Software Engineer at Google DeepMind, we look for the following skills and experience:

BS, MS or PhD degree in computer science, mathematics, applied stats, machine learning or similar experience working in industry
Experience working on software engineering projects from proof-of-concept through to implementation.
Proven knowledge and experience of Python, C++, GCL in production environments
Experience in applying experimental ideas to applied problems
Great communication skills and interpersonal skills
Knowledge of machine learning and statistics
Experience productionizing state-of-the-art large language and multimodal models a plus
Experience fine-tuning large models (e.g. SFT, RLHF, prompt optimization) a plus

The US base salary range for this full-time position is between $166,000 - $291,000 + bonus + equity + benefits. Your recruiter can share more about the specific salary range for your targeted location during the hiring process.

Note: In the event your application is successful and an offer of employment is made to you, any offer of employment will be conditional on the results of a background check, performed by a third party acting on our behalf. For more information on how we handle your data, please see our Applicant and Candidate Privacy Policy.

At Google DeepMind, we value diversity of experience, knowledge, backgrounds and perspectives and harness these qualities to create extraordinary impact. We are committed to equal employment opportunities regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy, or related condition (including breastfeeding) or any other basis as protected by applicable law. If you have a disability or additional need that requires accommodation, please do not hesitate to let us know.

Machine Learning Software Engineer, GeminiApp Agents and Tool Use