Senior Machine Learning Engineer (Python/MLOps)

We are a leader in technology services for companies in regulated industries with over 24 years of experience. We have completed hundreds of projects globally, focusing on life sciences, QA, validation, cloud systems, human capital management (HCM), and Salesforce. Our clients include Oriflame, Sanofi, Coca-Cola, and many others.

• At least 5 years of professional experience writing Python in software or ML engineering.
• Strong data engineering skills, SQL, and experience with workflow orchestration tools like Airflow or Spark.
• Proven track record of deploying and operating ML models in production, including serving infrastructure and monitoring.
• Solid software engineering fundamentals with clean, maintainable, well-tested code and collaborative development practices.
• Hands-on MLOps and CI/CD experience.
• Strong communication skills to work with Data Scientists and mentor others.
• Degree in Computer Science or related technical field, or equivalent practical experience.

Nice to have:

• AWS experience (S3, EC2, ECS).
• Docker and containerized environments.
• Experience with Ray or other distributed compute frameworks.
• REST API integration at scale.
• Familiarity with geospatial data.

• Own the deployment of new risk models and scores into production on Ray Serve and improve deployment maturity.
• Work with large-scale data sets and build custom workflows on existing platform foundations.
• Own data transformation pipelines converting semantic geospatial maps into attributes for categorical modelling.
• Collaborate with platform and infrastructure engineers to ensure reliable operation on large data sets and accelerated model inferencing.
• Embed MLOps and CI/CD best practices into the Insurance AI workflow and provide feedback to the central platform.