Security-Cleared ML Engineer – Public Sector

Scale AI; Washington (District of Columbia); On-site; USD 196,000 - 245,000; Full time

Benefits offered by this job

Health insurance

Equity in compensation

Generous PTO

Learning & Development stipend

Commuter stipend

Job summary

Scale AI in Washington, DC area seeks a Machine Learning Engineer to advance generative AI, computer vision, reinforcement learning, and agentic AI in production environments. You will leverage internal data infrastructure and massive datasets to improve Scale's products and customer experience, including the Public Sector ML efforts.

You’ll work with GenAI and LLMs, build scalable ML infra, and collaborate with product and research teams to prototype enhancements for government-facing products,

Qualifications

• 2+ years of experience building and deploying applied ML systems in production environments.
• Extensive experience with GenAI, Agentic AI, NLP, DL and RL, or CV in production.
• Strong algorithms, data structures, and OOP background.
• Proficient Python; experience with TensorFlow or PyTorch.

Responsibilities

• Take state of the art models and deploy in production to solve customer problems.
• Improve and maintain production models via retraining, tuning, and architecture updates.
• Collaborate with product and research teams to prototype ML-driven enhancements.
• Work with large datasets to develop generic and product-specific models.
• Build scalable ML infrastructure to automate ML services.

Skills

GenAI

Agentic AI

NLP

Computer Vision

Deep Learning

Reinforcement Learning

Python

TensorFlow

PyTorch

Tools

TensorFlow

PyTorch

Python

Job description

Scale AI in Washington, DC area seeks a Machine Learning Engineer to advance generative AI, computer vision, reinforcement learning, and agentic AI in production environments. You will leverage internal data infrastructure and massive datasets to improve Scale's products and customer experience, including the Public Sector ML efforts.

You’ll work with GenAI and LLMs, build scalable ML infra, and collaborate with product and research teams to prototype enhancements for government-facing products,