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Staff Research Engineer, AI Products - Mountain View
Mountain View, California, US
·
On-site
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Full-time
·
5d ago
Snapshot:
We are seeking a highly motivated and innovative Software Engineer to join us in rapidly exploring and implementing the state-of-the-art Gemini models across core Google products. You will work directly with engineering, product, and research teams in Google Deep Mind to quickly ideate, build, and iterate on proof-of-concept integrations that leverage cutting-edge AI capabilities. This role is about moving fast to validate new ideas, utilizing the latest advancements in multimodal large language models (vision, audio, text) to build functional, tangible prototypes. You will need to be a flexible, full-stack thinker, capable of jumping between different parts of the stack—from hacking together an agent harness for Gemini to quickly bringing up an end-to-end application demo for proving out product experiences. In this role, you will apply your broad engineering expertise to create the initial sparks that could eventually impact users globally.
About us:
Artificial Intelligence could be one of humanity’s most useful inventions. At Google Deep Mind, 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:
As a Software Engineer at Google Deep Mind, you will be at the forefront of translating research into tangible product concepts. You will drive the rapid development of experimental Gemini-powered features, pushing the boundaries of what's possible to create novel agentic services and “zero-to-one” engaging user experiences. Further, you will be collaborating with multiple product surfaces across Google to bring to life some of these experiences.
About you:
You are a passionate and talented software engineer with a versatile, full-stack AI skillset and a proven ability to rapidly prototype and iterate on ideas. You have a collaborative mindset and are excited to work as part of a team to tackle ambitious, undefined challenges. You are passionate about seeing AI research translated into real-world product concepts and are eager to work in an environment where speed of experimentation is key to long-term impact. You are a flexible thinker who can creatively solve problems up and down the stack to get compelling demos and experiences working in product form factor.
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Bachelors/Masters/Ph.D. in Computer Science, Artificial Intelligence, or a related field.
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A minimum of 5 years of relevant professional experience. Experience with core software engineering and building highly available, high-traffic production systems.
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Experience training, deploying and operating large machine learning models (LLMs or similar) in a high-scale, low-latency production environment. Solid understanding of distributed systems, cloud computing principles, and performance optimization.
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Proven track record in "zero-to-one" development—transforming raw ideas into rapid prototypes and full stack experience driving them through to full production.
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Strong programming skills in Python and C++.
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Experience with relevant ML frameworks such as JAX, Tensor Flow, or Py Torch, particularly for inference and serving.
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Excellent communication and collaboration skills.
In addition, the following would be an advantage:
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Full-stack engineering experience, comfortable working with frontend frameworks (e.g., React, Flutter, or simple web UIs) to visualize ideas, as well as backend services to power them.
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Strong track record in delivering features that leverage cutting-edge AI (e.g., LLMs, multimodal models) to a large user base.
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Deep understanding of end to end system architecture and adapting to new technologies and modern design
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Significant prompt engineering experience, deep understanding of evaluation strategies and familiarity with of pretraining, post-training concepts
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Familiarity with multimodal data and processing pipelines (vision, audio, text).
The US base salary range for this full-time position is between $197, 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 Deep Mind, 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.
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About Google DeepMind

Google DeepMind
AcquiredDeepMind Technologies Limited, trading as Google DeepMind or simply DeepMind, is a British-American artificial intelligence research laboratory which serves as a subsidiary of Alphabet Inc.
1,001-5,000
Employees
London
Headquarters
Reviews
3.8
10 reviews
Work Life Balance
3.8
Compensation
4.2
Culture
3.5
Career
4.0
Management
2.8
68%
Recommend to a Friend
Pros
Smart and brilliant colleagues
Good compensation and benefits
Work flexibility and remote options
Cons
Poor management and leadership issues
Bureaucracy and slow processes
Constantly changing priorities and goals
Interview Experience
5 interviews
Difficulty
3.0
/ 5
Duration
21-35 weeks
Offer Rate
60%
Experience
Positive 60%
Neutral 40%
Negative 0%
Interview Process
1
Application Review
2
Phone Screen/Online Assessment
3
Technical Interview
4
Team Matching Interview
5
Offer
Common Questions
Coding/Algorithm
Technical Knowledge
Behavioral/STAR
Research Experience
System Design
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