Senior ML Engineer - Public Sector, Security-Cleared

Scale AI; Washington; On-site; USD 226,000 - 282,000; Full time

Benefits offered by this job

Health, dental & vision coverage

Retirement benefits

Learning & development stipend

Generous PTO

Commuter stipend

Job summary

Scale AI in the United States is seeking a Senior Machine Learning Engineer to deploy GenAI, computer vision, and agentic AI models into production. You will improve products and customer experiences in mission‑critical environments, leveraging Scale's robust data and infra.

You will retrain models, tune hyperparameters, and update architectures while preserving core performance. Collaboration across product and research teams is essential, with heavy focus on large datasets and scalable ML

Qualifications

• Extensive experience with GenAI, agentic AI, NLP, DL, or CV in production.
• Strong algorithms, data structures, and OO programming.
• Proficient in Python; TensorFlow or PyTorch experience.

Responsibilities

• Deploy state-of-the-art models in production to solve customer problems.
• Retrain and tune models to maintain performance.
• Collaborate with product and research teams on ML-driven features.
• Work with large datasets to build generic and product-specific models.
• Build scalable ML infrastructure for automation.
• Advocate for ML techniques across engineering and product teams.
• Learn new technologies quickly and manage multiple priorities.

Skills

GenAI

Agentic AI

NLP

Deep Learning

Computer Vision

Education

Graduate degree in CS/ML

Tools

TensorFlow

PyTorch

Job description

Scale AI in the United States is seeking a Senior Machine Learning Engineer to deploy GenAI, computer vision, and agentic AI models into production. You will improve products and customer experiences in mission‑critical environments, leveraging Scale's robust data and infra.

You will retrain models, tune hyperparameters, and update architectures while preserving core performance. Collaboration across product and research teams is essential, with heavy focus on large datasets and scalable ML