Machine Learning Engineer (Defense)

The role

You will design and deploy production-grade systems that integrate machine learning models into scalable software pipelines. You will develop and ship features that leverage ML to solve real-world optimization and prediction problems using Kubernetes, AWS, and MLOps tooling.

What you will do

• Design and deploy production-grade systems that integrate machine learning models into scalable software pipelines
• Develop and ship features that leverage ML to solve real-world optimization and prediction problems
• Work with modern infrastructure like Kubernetes, AWS, and MLOps tooling
• Prioritize robustness, maintainability, and performance at scale

Required qualifications

• Proficiency in Python
• Experience with production ML tooling and frameworks (e.g., TensorFlow, PyTorch, scikit-learn)
• Experience using LLMs in production environments covering prompt engineering, fine-tuning, RAG systems, and frameworks like LangChain
• Strong understanding of data structures, algorithms, and software engineering best practices
• Familiarity with classical ML, deep learning with emphasis on transformer architectures, and MLOps concepts
• Experience building and maintaining scalable, reliable production ML systems with robust data pipelines, including expertise with Apache Beam, MLflow, and similar production-grade tools
• Commitment to high-quality ML engineering practices, including data versioning, experiment tracking, model governance, and automated testing pipelines
• Clear communication and collaboration across cross-functional teams

About the company

ASI is the frontier AI company that dynamically orchestrates critical infrastructure and defense assets, across air traffic control, energy, logistics, and combat operations. The company is headquartered in Boston with offices in Washington, DC, Denver, and Europe.