Machine Learning Engineer, Public Sector
About the role
Machine Learning Engineer at Scale focused on deploying cutting-edge models to mission-critical government systems, with emphasis on large language models and computer vision, across production environments and extensive datasets.
Responsibilities
- Take state of the art models developed internally and from the community, use them in production to solve problems for our customers and taskers
- Improve and maintain production models through retraining, hyperparameter tuning, and architectural updates, while preserving core performance characteristics
- Collaborate with product and research teams to identify and prototype ML-driven product enhancements, including for upcoming product lines
- Work with massive datasets to develop both generic models as well as fine tune models for specific products
- Build scalable machine learning infrastructure to automate and optimize our ML services
- Serve as a cross-functional representative and advocate for machine learning techniques across engineering and product organizations
- Be comfortable learning new technologies quickly and managing multiple priorities in a fast-paced environment
- Comfortable with light travel (approximately 10%) for customer interaction and team needs
Qualifications
- 2+ years of experience building and deploying applied ML systems in production environments
- Extensive experience with GenAI, Agentic AI, natural language processing, deep learning and deep reinforcement learning, or computer vision in a production environment
- Solid background in algorithms, data structures, and object-oriented programming
- Strong programming skills in Python, experience in Tensorflow or PyTorch
Skills
Benefits
- comprehensive health, dental and vision coverage
- retirement benefits
- a learning and development stipend
- generous PTO
- potential commuter stipend
About Scale AI
Data-centric infrastructure to accelerate the development of AI
Scale accelerates the development of AI within organizations of any size to deliver critical business insights and operational efficiency. Its data-centric infrastructure platform leverages RLHF (Reinforced Learning with Human Feedback) to help organizations build the strongest AI models that supercharge their business, with customers across industries including Meta, Microsoft, U.S. Army, DoD’s Defense Innovation Unit, Open AI, General Motors, Toyota Research Institute, Brex, Instacart and Flexport.
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