Machine Learning Engineer
Quick Summary
About Air Space Intelligence ASI's mission-critical technology powers decision-making across aviation, defense, energy, and other critical infrastructure domains.
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.
Responsibilities
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Proficiency in Python and experience with production ML tooling and frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
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Experience using LLMs in production environments — covering prompt engineering, fine-tuning, RAG systems, and frameworks like LangChain
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Strong understanding of data structures, algorithms, and software engineering best practices.
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Familiarity with classical ML, deep learning with emphasis on transformer architectures, and MLOps concepts.
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Experience building and maintaining scalable, reliable production ML systems with robust data pipelines, including expertise with Apache Beam, MLflow, and similar production-grade tools.
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Commitment to high-quality ML engineering practices, including data versioning, experiment tracking, model governance, and automated testing pipelines.
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A bias for simplicity and clarity in solving complex problems.
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Intellectual curiosity and willingness to collaborate.
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Clear communication and collaboration across cross-functional teams.
What We Offer
~1 min readWe 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.
Location & Eligibility
Listing Details
- Posted
- June 25, 2025
- First seen
- May 5, 2026
- Last seen
- May 8, 2026
Posting Health
- Days active
- 0
- Repost count
- 0
- Trust Level
- 14%
- Scored at
- May 6, 2026
Signal breakdown
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