Lead On-Device ML Engineer: Vision & GenAI

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
• 5 years of experience with software development in Python, and with data structures/algorithms.
• 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
• 3 years of experience with machine learning algorithms and tools (e.g., TensorFlow), artificial intelligence, deep learning, or natural language processing.
• Experience in Computer Vision/Audio, Machine Learning, and Deep learning.

Preferred qualifications:

• PhD in Computer Science or related technical field.
• 1 year of experience in a technical leadership role.
• Experience in training generative models (e.g., LLMs, GANs, diffusion models or audio language models).
• Proficiency in Tensorflow or PyTorch.
• Publications in CV/ML venues.

About the job

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.

We develop ML models for on-device ML solutions, bridging cutting-edge research with Google products. Our solutions enable a broad range of Google products (e.g., Background blur/replace in Meet via Web ML, Face AR effects in Duo and Meet, Pose Detection and Selfie Segmentation in ML Kit), and also enjoy great external adoption and visibility through our MediaPipe open source effort and many Google AI Blog publications.

On-device Solutions is part of the Core ML organization, which is responsible for machine learning at Google. With a broadened solutions mandate, we are expanding our ML offerings to enable even more high-impact Google’s products.

Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

The US base salary range for this full-time position is $161,000-$239,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

Responsibilities

• Bring state-of-the-art research in computer vision/audio including large generative models to Google products.
• Design efficient ML models and pipelines to power the next set of AI features in Google products.
• Collaborate closely with researchers and ML engineers across the Core ML On-Device Solutions organization, Research, DeepMind, as well as our partners in Pixel, Meet, Photos, Youtube, etc.