Mission-Critical AI Engineer for Defense Tech

Craigslist (sfbay); San Francisco (CA); On-site; USD 120,000 - 190,000; Full time

Job summary

United States Digital Space LLC is hiring an AI Engineer to design, train, and deploy advanced ML models for mission-critical workflows in defense-oriented environments. You will build end-to-end data pipelines and production-ready systems, emphasizing reliability, testing, and observability.

The role demands strong software engineering fundamentals and hands-on experience with PyTorch, TensorFlow, and Hugging Face, plus a solid ML principles foundation and real-world data handling skills.

Qualifications

• Bachelor’s degree (B.Sc.) in Computer Science or related field.
• Strong software engineering fundamentals.
• Solid understanding of machine learning principles (model evaluation, optimization, bias/variance tradeoffs).
• Hands-on experience with ML frameworks (PyTorch, TensorFlow, Hugging Face).
• Experience working with real-world data.

Responsibilities

• AI/ML Development: Design, train, fine-tune, and deploy state-of-the-art ML models to solve real-world operational problems.
• Data & Systems Engineering: Build scalable data pipelines for structured and unstructured data (text, imagery, geospatial, sensor data).
• Engineering Excellence: Integrate models into robust, scalable production systems with strong testing, observability, and CI/CD practices.
• Research & Experimentation: Prototype and benchmark new modeling approaches (LLMs, multimodal systems, RAG) to improve performance, robustness, and mission impact.

Skills

Strong software engineering

ML principles

ML frameworks

Education

Bachelor’s degree (B.Sc.) in Computer Science

Tools

PyTorch

TensorFlow

Hugging Face

Job description

United States Digital Space LLC is hiring an AI Engineer to design, train, and deploy advanced ML models for mission-critical workflows in defense-oriented environments. You will build end-to-end data pipelines and production-ready systems, emphasizing reliability, testing, and observability.

The role demands strong software engineering fundamentals and hands-on experience with PyTorch, TensorFlow, and Hugging Face, plus a solid ML principles foundation and real-world data handling skills.