Snapshot:
Our team is part of Google DeepMind and is focused on improving Gemini models for agentic capabilities such as Deep Research. We work on planning, reasoning, tool use and writing quality. Our team is composed of a mix of software engineers and research scientists who work closely to improve models and products. Our team launched Deep Research creating a new product category that found significant traction. The team works on constantly improving Deep Research and adding meaningful features to delight our users. The team has also contributed significantly in improving Gemini’s web browsing capabilities.
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:
Join our Deep Research team and revolutionize how research is conducted. As an Applied ML Software Engineer, you will harness the power of Gemini models to build the most advanced and reliable research agent on the market.
You will be responsible for:
- Designing Intelligent Agents: Create and implement sophisticated agentic workflows that allow our models to intelligently use tools and data to solve complex problems.
- Pragmatic System Design: Make critical design trade-offs based on a deep understanding of model capabilities and limitations. You'll architect systems that are not just theoretically sound but are also cost-effective, reliable, and delightful for users at scale.
- Driving Model Improvement: Develop robust evaluation systems, autorating mechanisms, and synthetic data pipelines to ensure our models are constantly learning and improving.
- End-to-End Feature Ownership: Shepherd new agent capabilities from initial ideation and prompt engineering, through system design and implementation, to launch and post-launch analysis. You will be the expert on the "why" behind a feature, not just the "how."
- Pushing the Boundaries of LLMs: Experiment with novel post-training techniques to unlock new capabilities and efficiencies in our models.
- Elevating the Team: Mentor and guide fellow team members, contributing to a culture of technical excellence and innovation.
About you:
You are a talented and resourceful engineer capable of applying large language models at scale; conceiving of and executing experiments to improve them; and overcoming last mile issues to launch your model into production for millions of people to use. 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.
- Experience productionizing state-of-the-art large language and multimodal models, prompt optimization.
- Knowledge of LLMs, machine learning and statistics
- Experience in applying experimental ideas to applied problems
- Required programming languages: Python; C++
- Great communication skills and interpersonal skills
- Experience post training large models (e.g. SFT, RL)
The US base salary range for this full-time position is between $166,000-244,000 + 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.
