Principal Engineer, Applied Machine Learning, Core Machine Learning

Key Skills

Aartificial intelligence, Analytical and Problem solving, Applied Machine Learning, Cloud computing, CoreML, Data Modeling, Data science techniques, Design, Digital Innovation, Edge AI, Google Cloud Platform (GCP), Google Products, Growth Analytics, HTTP acceleration, Infrastructure as code, Internet Ads, Large Language Models - LLMs, Leadership, Machine learning techniques, Mathematics, Mentoring, Optimization, Planning and organization, Product Development, Search Engine, Translation

Job Description

Minimum qualifications:

• Bachelor's degree in Computer Science, Mathematics, other relevant engineering field, or equivalent practical experience
• 15 years of experience as a Software Engineering leader in ML Infrastructure, ML or AI for products, or related fields
• Experience with machine learning systems
• Experience motivating others at all levels by creating a roadmap

Preferred qualifications:

• Experience building ML infrastructure or products with heavy use of AI/ML and large groups of stakeholders or users
• Experience in large language model, media generation, or other generative AI tuning and optimization techniques
• Experience with working with stakeholders to understand their needs and translate them into technical requirements
• Experience with ideation and innovation of technology at scale and passion for development and the use of cross-platform shared code
• Understanding of ML Systems and Infrastructure for production with technical knowledge to be credible with customers and engineers

About the job

The mission of the Applied Machine Learning Organization at Core Machine Learning (CoreML) is to provide a guide to accelerate Machine Learning (ML) research to production. We build standardized ML tool chains and platforms, powered with production-grade models and advanced ML techniques, and flow research innovations to products through general purpose or specific use case tuned models. We directly engage with many Product Areas across Alphabet and land models and techniques with significant quality, performance, and productivity wins.

As a Principal Engineer, you will be responsible for technical design and outlook for our Generative AI tuning and optimization platform. You will be deeply involved in the long-term design and experience of our tuning and adaptation workflow that brings the best in AI to the right Google products.

Google Cloud accelerates organizations’ ability to digitally transform their business with the best infrastructure, platform, industry solutions and expertise. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology – all on the cleanest cloud in the industry. 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 $271,000-$399,000 + 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

• Lead the technical design across the team as needed to build Generative AI tuning and optimization platforms to improve model quality and performance, as well as providing a guide for research innovations to be translated into safe and reliable products.
• Work with partners from Google Research and Product Areas (e.g., Ads, Search, YouTube, Cloud, etc.), to develop Generative AI tuning and optimization tool chains, platforms, and techniques. Influence partners and stakeholders across the organization to build joint roadmaps and drive outcomes for product.
• Lead, design, and develop the Generative AI Model to Production strategy in alignment with Core ML strategy.
• Mentor and train team members on system design, ML modeling, and coding techniques relevant to Generative AI. Keep the team current with knowledge and models, and help prioritize technical innovation accordingly.