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Software Engineer II, Machine Learning Systems - Insight Global
ML Engineer
Develop and maintain machine‑learning integration pipelines for non‑destructive testing workflows, ensuring reproducible, stable deployments of visual, ultrasonic, and eddy‑current inspection data using modern cloud and container technologies.
About the role
Key Responsibilities
- Design, implement, and maintain end‑to‑end ML pipelines that ingest and process inspection data (visual, ultrasonic, eddy‑current) for pilot deployments.
- Containerize ML components using Docker and orchestrate them with Kubernetes to guarantee reproducibility and scalability.
- Develop CI/CD workflows to automate testing, building, and deployment of ML services in cloud environments.
- Collaborate with data scientists and domain experts to translate research prototypes into production‑ready systems.
- Monitor, troubleshoot, and optimize performance of deployed ML workflows, ensuring reliability and low latency.
Requirements
- Strong programming experience in Python and C++ for building ML integration code.
- Hands‑on experience with Docker, Kubernetes, and cloud platforms such as AWS.
- Proficiency in creating CI/CD pipelines (e.g., Jenkins, GitLab CI, GitHub Actions).
- Understanding of non‑destructive testing data types and ability to work with image and signal processing pipelines.
- Bachelor’s degree in Computer Science, Engineering, or related field and 2+ years of software engineering experience in ML systems.
Skills
pythoncdockerkubernetescicdaws