3 months ago
Base Salary
$226k - $282k/yr
Responsibilities
- Deploy internally developed and community-developed models to solve customer and tasker problems in production.
- Improve and maintain production models through retraining, hyperparameter tuning, and architectural updates.
- Collaborate with product and research teams to identify and prototype ML-driven product enhancements.
- Develop generic models and fine-tuned models using massive datasets.
- Build scalable machine learning infrastructure to automate and optimize ML services.
- Represent and advocate for machine learning techniques across engineering and product organizations.
- Learn new technologies quickly and manage multiple priorities in a fast-paced environment.
- Travel approximately 10% for customer interaction and team needs.
- Maintain an active security clearance.
Requirements
- Extensive production experience with generative AI, agentic AI, natural language processing, deep learning, deep reinforcement learning, or computer vision.
- Strong background in algorithms, data structures, and object-oriented programming.
- Strong programming skills in Python.
- Experience with TensorFlow or PyTorch.
- Graduate degree in Computer Science, Machine Learning, or an Artificial Intelligence specialization is preferred.
- Experience with AWS or GCP and deploying machine learning models in cloud environments is preferred.
- Experience with computer vision, generative AI models, large language models, or agentic systems is preferred.
- Familiarity with machine learning evaluation frameworks and agentic model design is preferred.
- An active security clearance is required.
Benefits
- Comprehensive health, dental, and vision coverage.
- Retirement benefits.
- Learning and development stipend.
- Generous paid time off.
- Potential commuter stipend eligibility.
- Approximately 10% travel and full-time employment in Washington, DC.
- The role requires an active security clearance.
Tech Stack
Categories
About Scale AI
Scale AI builds data annotation services and AI development tools for enterprises and government agencies, sold as a platform and managed services. Its products include the Scale Generative AI Platform for building and evaluating agents and the Data Engine for collecting, curating, and labeling training data, including RLHF and model evaluation. Founded in 2016 and headquartered in San Francisco, the company is privately held and works across domains from computer vision to LLM applications.