Director, ML/AI Solutions, Google Public Sector
Qualifications
Minimum qualifications:
- 15 years of experience applying AI solutions and ML-related technologies to solve real-world AI/ML problems in consumer or enterprise applications
- Experience with LLMs, Open Source framework (e.g., Jax, PyTorch), big data and machine learning frameworks, and numerical programming frameworks (e.g., Python or MATLAB)
- Experience with responsible AI practice and ML technologies
Preferred qualifications:
- Knowledge of technical trends, with the ability to adapt to new AI/ML technologies and apply them to consumer or enterprise applications
- Ability to partner effectively across organizational boundaries, build relationships, and import/export talent and ideas to achieve broader organizational goals
- Ability to build outlooks and drive technical roadmap, and design with a broader engineering organization
- Ability to learn quickly, understand, and work with emerging technologies, methodologies, and solutions in the Cloud/IT technology space
- US Government TS/SCI clearance
About the job
Google Public Sector (GPS) provides public sector organizations with leading cloud capabilities and industry solutions. We deliver enterprise-grade cloud solutions that leverage Google’s technology to help public sector agencies operate more efficiently and adapt to changing needs, giving customers a foundation for the future. Customers turn to GPS as their trusted partner to solve their most critical problems.
As Director, you will play an integral role in connecting Google capabilities to our customers. Guided by , we believe our approach to Artificial Intelligence (AI) must be both bold and responsible. Google Public Sector strives to work together with our government partners to ensure they are using enterprise-grade AI offerings that protect their data and IP ownership, while also adhering to Responsible AI design.
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 $256,000-$375,000 + 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
- Support development of strategies to drive business growth through the creation of innovative AI/ML solutions. Provide in-depth AI expertise to support the technical relationship with Google’s customers, including product and solution briefings, creating demos, proof-of-concept work, and partner directly with product management to prioritize solutions impacting customer adoption to Google Cloud.
- Work directly with customers to demonstrate and prototype Google Cloud AI product integrations in customer/partner environments.
- Recommend integration strategies, enterprise architectures, platforms and application infrastructure required to successfully implement a complete AL/ML solution using best practices on Google Cloud.
- Support developers, creators, and enterprises to leverage Google’s Generative Language APIs so they can build their own future AI products.
- Collaborate closely with product management and engineering peers to align on product releases and build core capabilities into reusable solutions.
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