US: $174000 - $252000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google.
Build scalable offline and online multi-modal data and serving pipelines integrating camera/video intelligence, HomeGraph device state, and telemetry to supply high-value signals to Home Context and HFM.
Design, develop, and productionize Home Context capabilities (such as Home Pulse, household routine modeling, and anomaly detection) and integrate them with flagship Google Home features including Visual Home Brief and Camera Captions.
Partner closely with Research and Infrastructure teams to co-develop, evaluate, and productionize the Home Foundation Model (HFM) for real-world Smart Home applications.
Integrate contextual understanding with Identity and Presence signals so downstream Home experiences understand the user.
Collaborate with Product, Research, and Vertical engineering teams to define target use cases, build evaluation benchmarks, and drive model and system quality improvements from prototype to launch.
Minimum qualifications
Bachelor’s degree or equivalent practical experience.
5 years of experience with software development in one or more programming languages.
3 years of experience with end-to-end Machine Learning (e.g., model deployment, model evaluation, data processing, debugging).
3 years of experience with one or more of the following: Speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
Experience designing and operating distributed computing systems for large-scale AI/ML workloads.
Preferred qualifications
Master's degree or PhD in Computer Science or related technical field.
1 year of experience in a technical leadership role.
Experience partnering with research teams to transition novel models into scalable, low-latency production services.
Experience taking Machine Learning and Generative AI features from prototype to production environments.
Experience with Generative AI techniques, including foundation models, multi-modal modeling, and vision modeling.
Experience developing accessible technologies.
Bachelor’s degree or equivalent practical experience.
5 years of experience with software development in one or more programming languages.
3 years of experience with end-to-end Machine Learning (e.g., model deployment, model evaluation, data processing, debugging).
3 years of experience with one or more of the following: Speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
Experience designing and operating distributed computing systems for large-scale AI/ML workloads.
