Machine Learning Engineer (Defense)

ASI's mission-critical technology powers decision-making across aviation, defense, energy, and other critical infrastructure domains. Backed by top-tier investors including Andreessen Horowitz, Spark Capital, and Renegade Partners, ASI delivers operational decision superiority—compressing days of analysis into seconds of action. ASI is leading the way and pushing the boundaries of what's possible.

• Proficiency in Python and 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.
• A bias for simplicity and clarity in solving complex problems.
• Intellectual curiosity and willingness to collaborate.
• Clear communication and collaboration across cross-functional teams.

We look at the interview process not as screening test but rather as an opportunity to simulate what it would look like working together. We build the interview process around you.

ASI works with export controlled technology and restricted U.S. Government data, including on contracts mandating U.S. immigration status and location restrictions for performing personnel. Employment offers are contingent on ability to timely obtain all required authorizations for contemplated job duties.