Research Engineering Manager at DeepMind

Mountain View, California, United States -

Full Time

Start Date

Immediate

Expiry Date

16 Jan, 26

Salary

349000.0

Posted On

18 Oct, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Large Language Models, Technical Leadership, Project Management, Collaboration, Communication, Deep Learning, Python, TensorFlow, PyTorch, JAX, AI Ethics, Safety, Innovation, Strategic Planning, Data Processing

Industry

Research Services

Description

Snapshot We are hiring a Research Engineering Manager to focus on a range of research projects within the Responsibility portfolio at Google DeepMind. This role is crucial for fulfilling Google DeepMind's mission to build AI responsibly to benefit humanity. The position involves leading teams, defining technical direction, and ensuring high-impact delivery across multiple projects that advance responsible AI development. 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 We’re looking for an experienced Engineering Manager to lead and contribute to key research projects within our Responsibility portfolio. You will manage a team of Research Engineers, fostering a culture of innovation and collaboration. You will be responsible for setting the technical vision, guiding project execution, and ensuring alignment with Google DeepMind's broader strategy for responsible AI. This role requires a unique blend of deep technical expertise in Machine Learning and Large Language Models, strong leadership skills, and the ability to navigate complex projects and stakeholder landscapes. You will work closely with Research Scientists, Product Managers, and other engineering teams to deliver impactful results and communicate progress effectively to both technical and executive audiences. Key responsibilities: Lead, mentor, and grow a team of Research Engineers. Define and drive the technical strategy and roadmap for research projects within the Responsibility portfolio. Oversee the design, development, and implementation of robust and scalable ML systems and tools. Ensure projects are well-defined, resourced, and executed efficiently to meet research and organizational objectives. Collaborate with cross-functional teams (e.g., Research, Product, Policy) to identify and address key challenges in responsible AI. Communicate complex technical concepts, project statuses, risks, and opportunities clearly and concisely to various stakeholders, including researchers, engineers, and executive leadership. Foster strong relationships with internal and external collaborators. Stay abreast of the latest advancements in AI, machine learning, LLMs, and AI ethics and safety. Connect project work to the organization's strategic goals for responsible AI development. About You In order to set you up for success as a Research Engineering Manager at Google DeepMind, we look for the following skills and experience: 7+ years of experience in a technical leadership role, with at least 3 years of experience managing engineering teams. Bachelor's degree in Computer Science, Engineering, Machine Learning, or a related technical field, or equivalent practical experience. Proven track record of leading and delivering complex, large-scale machine learning projects. Deep understanding and hands-on experience with state-of-the-art Machine Learning techniques, particularly in Deep Learning and Large Language Models (LLMs). Strong programming skills, preferably in Python, and experience with common ML frameworks (e.g., TensorFlow, PyTorch, JAX). Excellent communication and interpersonal skills, with the ability to explain technical concepts to both technical and non-technical audiences, including executive leadership. Experience in strategic planning and connecting technical projects to broader organizational goals. Ability to work flexibly across multiple projects and adapt to evolving priorities. In addition, some of the following would be an advantage: Master's or PhD in Computer Science, Machine Learning, or a related field. Experience working in AI ethics, safety, or responsibility research. Experience with large-scale data processing and distributed systems. Publications or contributions to the machine learning research community. Experience working in a fast-paced, research-driven environment. Familiarity with the sociotechnical aspects of AI systems. The US base salary range for this full-time position is between $248,000 - $349,000 + bonus + equity + benefits. Your recruiter can share more about the specific salary range for your targeted location during the hiring process. Application deadline: Friday 31st October 2025 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 opportunity 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.

Responsibilities

Lead and mentor a team of Research Engineers while defining and driving the technical strategy for research projects. Collaborate with cross-functional teams to ensure efficient project execution and alignment with organizational goals.