Staff Research Engineer, Expressive Motion and Believability, DeepMind
San Francisco, CA, United StatesYesterday
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Key details
- Salary
- $207K–$300K/yr
- Location
- San Francisco, CA, United States
- Work style
- Onsite
- Level
- Senior
- Experience
- 8–11 yrs
- Function
- Software engineering
- Focus area
- other
- Posted
- Yesterday
Skills
About the role
About the job
As a Research Engineer on the Companion Robots team, you will train expressive, emotionally legible motion—including gait, gaze, posture, and gesture that change visibly with the robot's internal state—and develop the metrics to evaluate its effectiveness. You will work directly with animators and character designers, utilizing their expertise as a tuning pass and training signal, while building the evaluation harness required to compare behaviors, models, and robot platforms. Furthermore, you will collaborate with our state-of-the-art video generation and interaction models, such as Omni or Code Genie, to create systems capable of generating real-time expressive behavior in response to stimuli and internal motivations.
Artificial intelligence will be one of humanity’s most transformative inventions. At Google DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users. We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority.
US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Work with omni/omni-live to extract animation, fine tune models to generate real time behavior and expression in response to stimulus and internal motivation of the character.
- Design, train and evaluate reinforcement learning and imitation learning algorithms for lifelike movement, gaze and posture, conditioned on the robot's affective and motivational state.
- Work with animators to convert a library of hand-authored reference motion into style-conditioned policies, using adversarial motion priors and related techniques, so that character can be authored rather than hand-tuned.
- Create scenario suites, batch simulation, video capture, and automated critics that assess behavior reads correct to an observer.
- Run paired human comparisons with designers and human-factors partners, and report how well automated critics correlate with human judgment.
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 8 years of experience in software development.
- 5 years of experience testing, and launching software products.
- 3 years of experience with software design and architecture.
- 2 years of experience in reinforcement learning, imitation learning, multimodal generative modeling, training and inference, and large vision, vision-language, video, and other multimodal models.
- 1 year of experience building generative architectures or world models applied to video, robotics, or interactive simulation environments.
Preferred qualifications:
- Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
- 8 years of experience with data structures and algorithms.
- 3 years of experience in a technical leadership role leading project teams and setting technical direction.
- 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.
- Bachelor’s degree or equivalent practical experience.
- 8 years of experience in software development.
- 5 years of experience testing, and launching software products.
- 3 years of experience with software design and architecture.
- 2 years of experience in reinforcement learning, imitation learning, multimodal generative modeling, training and inference, and large vision, vision-language, video, and other multimodal models.
- 1 year of experience building generative architectures or world models applied to video, robotics, or interactive simulation environments.