Staff Research Engineer, Expressive Motion and Believability, DeepMind

Google•Mountain View, CA

3d•$207,000 - $300,000

About The Position

As a Research Engineer on the Companion Robots team, you will train expressive, emotionally legible robot motion—including gait, gaze, posture, and gesture that visibly responds to the robot’s internal state—and develop metrics to evaluate its effectiveness. You will work directly with animators and character designers, using their expertise as a tuning pass and training signal, while building evaluation tools to compare behaviors, models, and robot platforms. You will also collaborate with video-generation and interaction models, such as Omni or Code Genie, to create systems that generate real-time expressive behavior in response to stimuli and internal motivations. Google DeepMind is an interdisciplinary AI lab focused on advancing AI to address complex global challenges and accelerate product innovation. The organization describes public benefit, scientific discovery, safety, and ethics as priorities. Individual pay is determined by factors including job-related skills, experience, and relevant education or training. The stated US pay range is $207,000–$300,000, with a 20% bonus target, equity, and benefits.

Requirements

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.

Nice To Haves

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.

Responsibilities

Work with Omni/Omni-Live to extract animation and fine-tune models to generate real-time behavior and expression in response to stimuli and a character’s internal motivations.
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 hand-authored reference motion into style-conditioned policies using adversarial motion priors and related techniques, enabling characters to be authored rather than hand-tuned.
Create scenario suites, batch simulation, video capture, and automated critics to assess whether behavior reads correctly to an observer.
Run paired human comparisons with designers and human-factors partners, and report how well automated critics correlate with human judgment.