ASI enables success for the world's most complex operations. From critical infrastructure to defense, we serve major airlines and U.S. and allied government organizations, providing our partners with a decision advantage from planning to operations. Backed by top-tier investors—including Andreessen Horowitz, Spark Capital, and Renegade Partners—we are boldly investing in R&D and growth to push the boundaries of what’s possible.
What you will do:
As part of our core 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).
- Strong understanding of data structures, algorithms, and software engineering best practices.
- Familiarity with classical ML, deep learning, and MLOps concepts.
- Experience building and maintaining scalable, reliable systems that include ML components.
- 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 a screening test but rather as an opportunity to simulate what it would look like working together. We build the interview process around you.
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