Senior Machine Learning Engineer (Python/MLOps)

Workplace: hybrid, Warsaw

Type of Contract: B2B

Join our fast-growing team as a Senior Machine Learning Engineer and shape the future of geospatial data analysis using a cutting‑edge tech stack, including Ray Serve and AWS. In this role, you will take full engineering ownership of deploying advanced AI models, transforming raw data at a scale of hundreds of millions of rows into reliable, real‑time services.

Key Responsibilities

• Owning the deployment of new risk models and scores into production on Ray Serve, and lifting the Insurance AI team's deployment maturity.
• Working with large‑scale data sets (hundreds of millions of rows) and building custom workflows on top of existing platform foundations.
• Owning data transformation pipelines that turn semantic geospatial maps of a property into attributes suitable for categorical modelling.
• Collaborating with platform and infrastructure engineers to ensure solutions run reliably on our large data sets and accelerated model inferencing.
• Embedding MLOps and CI/CD best practice into the Insurance AI workflow, and feeding requirements back into the central platform.

Required Skills and Experience

• At least 5 years of industry experience writing Python in a professional software or ML engineering context.
• Strong data engineering skills, SQL, and hands‑on experience with workflow orchestration tools such as Airflow, Spark, or similar.
• A track record of deploying and operating ML models in production, including serving infrastructure, monitoring, and the realities of keeping models healthy over time.
• Solid software engineering fundamentals: clean, maintainable, well‑tested code, and fluency in a shared codebase (feature branches, pull request reviews, collaborative development).
• Hands‑on MLOps and CI/CD experience.
• Strong communication skills, including the ability to work with Data Scientists and other non‑platform engineers without losing the technical plot, and to mentor others in good engineering practice.
• A degree in Computer Science or a related technical field, or equivalent practical experience.

Nice to have

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

What do we offer?

• Benefits package (private health insurance, sports card, group insurance).
• Free English lessons with a dedicated teacher.
• Access to an extensive training library covering both soft and technical skills.
• Sports activities.
• Team‑building events, contests, and challenges.
• Sales Incentive Program and Refer‑a‑Friend Program.