Machine Learning Engineer (Defense)
Air Space Intelligenceover 1 year ago
Boston, MA, USASenior
Responsibilities
- Design and deploy production-grade systems integrating machine-learning models into scalable software pipelines.
- Develop and ship ML-powered features for real-world optimization and prediction problems.
- Build reliable production ML systems and robust data pipelines using modern infrastructure and MLOps tooling.
- Prioritize robustness, maintainability, and performance at scale.
Requirements
- Proficiency in Python and experience with production ML tooling and frameworks such as TensorFlow, PyTorch, and scikit-learn.
- Production experience with LLMs, including prompt engineering, fine-tuning, RAG systems, and LangChain.
- Strong understanding of data structures, algorithms, and software engineering best practices.
- Familiarity with classical machine learning, deep learning with an emphasis on transformer architectures, and MLOps concepts.
- Experience building and maintaining scalable, reliable production ML systems and robust data pipelines, including Apache Beam and MLflow.
- Knowledge of data versioning, experiment tracking, model governance, and automated testing pipelines.
- Clear communication, collaboration, intellectual curiosity, and a commitment to simple, maintainable solutions.
- Ability to obtain required authorizations for work involving export-controlled technology and restricted U.S. Government data, including applicable immigration status and location requirements.
Tech Stack
Categories
About Air Space Intelligence
Air Space Intelligence builds decision-support software that lets operators simulate scenarios, predict risk, and optimize logistics and operations across aviation, defense, energy, and other critical infrastructure. The company sells enterprise platforms to government and commercial customers, including programs requiring U.S. security clearances. Founded in 2018 and headquartered in Boston, it is privately held and backed by investors such as Andreessen Horowitz, Spark Capital, and Renegade Partners.