Senior Machine Learning Engineer

Air Space Intelligence is a company with a global engineering team working on production-grade systems that integrate machine learning models into scalable software pipelines, leveraging infrastructure like Kubernetes, AWS, and MLOps tooling.

• Proficiency in Python and experience with production ML tooling and frameworks such as TensorFlow, PyTorch, scikit-learn.
• Experience using LLMs in production including 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 focusing on transformer architectures, and MLOps concepts.
• Experience building and maintaining scalable, reliable production ML systems with robust data pipelines using tools like Apache Beam, MLflow.
• Commitment to ML engineering practices including data versioning, experiment tracking, model governance, and automated testing pipelines.
• Intellectual curiosity, willingness to collaborate, and clear communication skills.

• Design and deploy production-grade systems integrating machine learning models into scalable software pipelines.
• Develop and ship features leveraging machine learning to solve real-world optimization and prediction problems.
• Work with modern infrastructure such as Kubernetes, AWS, and MLOps tooling.
• Maintain robustness, maintainability, and performance of ML systems at scale.
• Collaborate clearly across cross-functional teams.