AI/ML Engineer, Public Sector
1 week ago
- Bachelor's degree in Engineering, Computer Science, a related field, or equivalent practical experience.
- 6 years of experience with machine learning model development and deployment, frameworks (e.g., PyTorch, TensorFlow, Jax, Ray, etc.), AI accelerators (e.g., TPUs, GPUs), model architectures (e.g., encoders, decoders, transformers), and using machine learning Application Programming Interface (APIs).
- 6 years of experience in working with technical customers.
- Experience with Python.
- Active Top Secret/SCI US government security clearance.
- Experience in optimizing Large Language Model (LLMs) leveraging Retrieval Augmented Generation (RAG) architectures and fine-tuning techniques.
- Experience in building solutions for national security customers.
- Experience in working with multiple clouds.
- Experience in C++ programming language.
- Experience in Linux/Unix.
- Ability to lead design and implementation of AI-based solutions, web services, and debugging tools and containerize ML workloads.
In this role, you will focus on ensuring the quality of customer engagements, while building excellent relationships with key stakeholders both internally and externally. These relationships will help your team meet the customer's technical requirements and business objectives. You will deliver and execute leading by example to ensure customers in your region succeed.
Google Public Sector brings the magic of Google to the mission of government and education with solutions purpose-built for enterprises. We focus on helping United States public sector institutions accelerate their digital transformations, and we continue to make significant investments and grow our team to meet the complex needs of local, state and federal government and educational institutions.
The US base salary range for this full-time position is $147,000-$216,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. 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:- Act as a trusted technical advisor to customers and solve machine learning tests.
- Create and deliver recommendations, tutorials, blog articles, sample code, and technical presentations adapting to different levels of business and technical stakeholders.
- Work with Customers, Partners, and Google Product teams to deliver solutions into production.
- Coach customers on the practical tests in Machine Learning systems like feature extraction/feature definition, data validation, monitoring, and management of features/models.
- Travel up to 30% of the time in-region for meetings, technical reviews, and onsite delivery activities as needed.
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