
Machine Learning Engineer (Defense) at Air Space Intelligence (Boston, MA)
Air Space Intelligence· Boston, MA·
Role details
Summary
Design and deploy production-grade systems integrating machine learning models into scalable software pipelines for defense engineering. Develop features leveraging ML to solve optimization and prediction problems using modern infrastructure like Kubernetes and AWS.
Job description
About ASI
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. What You Will Do: As part of our Defense engineering team, you will design and deploy production-grade systems that integrate machine learning models into scalable software pipelines. You’ll develop and ship features that leverage ML to solve real-world optimization and prediction problems, working with modern infrastructure like Kubernetes, AWS, and MLOps tooling. You’ll approach problems with a software engineer’s mindset—prioritizing robustness, maintainability, and performance at scale.
What We Value:
- 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.
How We Hire: 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.
Why work at Air Space Intelligence
- Culture: High-energy, mission-driven environment where “speed matters” and autonomy is granted early. Emphasizes merit over experience, intellectual curiosity, and resourceful builders.
- Work policy: Flexible work hours and flexible time off (output-based). Offices in Boston, Gdansk, and Washington, D.C. – likely hybrid/remote-friendly (global team supporting 24/7 operations).
- Perks: Premium healthcare, competitive salary + equity, team lunches, ergonomic office equipment, and modern productivity tools.
- Engineering culture: Strong focus on impactful work (systems already monitoring tens of thousands of flights globally), collaboration across distributed teams, and a mantra of “today is better than tomorrow.”
- Ratings: 4.7/5 on LinkedIn (6 reviews), with high marks for culture (4.8), compensation, and work-life balance (4.6).