Design, build, and operationalize artificial intelligence and machine learning solutions for enterprise clients, combining custom models with cloud and third-party AI services to deliver production-ready outcomes.
Responsibilities
Formulate real-world problems into practical, efficient, and scalable AI and Machine Learning solutions
Develop and implement machine learning algorithms, models, and computational systems
Design and build scalable data pipelines to support model training and production with DevOps & MLOps
Customize and apply Deep Learning and Gen AI models for various use cases
Engage in research and development of new AI and high-performance compute algorithms, models, and simulations
Design, develop, and test software that is used to both control and simulate SpaceX flight systems for the Starship spacecraft.
Responsibilities
Develop highly reliable autonomous software systems and the simulations required to validate them
Own all aspects of software development, including design, testing, and integration to the mission
Work with counterpart engineering teams to develop and maintain launch and vehicle software, crossing all required software domains necessary to implement and verify control of the pad, ship, and booster to meet mission objectives
Follow and maintain high software standards and software engineering best practices within Starship Software
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.
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.
Requirements
Bachelor’s degree in Computer Science or related field
Nice to have: Master's degree or PhD in Computer Science or related technical field
Nice to have: technical leadership experience
Nice to have: partnering with research teams
Nice to have: Machine Learning modeling
Nice to have: Distributed Machine Learning system design
Staff Software Engineer, AI/ML, ML Infrastructure, Search AdsNewGoogle · Mountain View, US+1 more
Software Engineer, Flight Software (Starship)SpaceX · Cape Canaveral, US