US: $147000 - $210000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google.
Design, develop, test, and deploy robust, production-grade ML models and infrastructure.
Build, own and maintain scalable data pipelines, feature stores, and automated training/evaluation workflows to support continuous model iteration.
Partner closely with Product Managers, Data Scientists and other ML Engineers to translate requirements into concrete technical solutions.
Monitor, benchmark, and optimize production ML models for latency, throughput, and cost-efficiency without compromising prediction quality.
Minimum qualifications
Bachelor’s degree or equivalent practical experience.
2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree.
1 year of experience with one or more of the following: LLM systems, 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.
1 year of experience with AI/ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
Preferred qualifications
Master's degree or PhD in Computer Science or related technical fields.
2 years of experience with data structures or algorithms.
Experience developing accessible technologies.
Bachelor’s degree or equivalent practical experience.
2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree.
1 year of experience with one or more of the following: LLM systems, 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.
1 year of experience with AI/ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
