Machine Learning Engineer

About Air Space Intelligence

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.

We are modernizing America’s air traffic control system on an accelerated timeline, tackling one of the world’s most complex real-time optimization challenges: safely coordinating tens of thousands of daily flights in a dynamic, safety-critical environment. Our team is building next-generation trajectory prediction and decision-support systems while preparing the airspace for emerging technologies like commercial space operations and advanced air mobility. This mission-critical work demands exceptional precision, resilience, and reliability to support the safety and efficiency of the national airspace.

What You Will Do:

As a Machine Learning Engineer, 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 a screening or 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.