
Senior Data Scientist
5 days ago
Developing cutting-edge machine learning solutions is a highly complex task that requires a high degree of technical expertise and understanding of the ML lifecycle.
A key challenge in this area is the need for robust infrastructure that can handle large amounts of data and scale accordingly. This is where the role of an ML Platform Engineer comes in, responsible for designing and implementing scalable platforms that empower data scientists to build and run machine learning pipelines efficiently.
The ideal candidate will have a strong background in software engineering, with experience in developing production-grade ML libraries, algorithms, and CLI tooling. Familiarity with MLOps frameworks such as Azure DevOps, Databricks, and FastAPI is also essential, as well as a solid understanding of orchestration patterns and scalable ML infra.
As an ML Platform Engineer, you will be working closely with data scientists and engineers to improve the developer experience, optimize data ingestion and feature engineering processes, and automate workflows using CI/CD processes. The successful candidate will be able to design clean, modular APIs and internal tools, as well as collaborate effectively within a global, diverse team.
- Design and implement scalable ML infrastructure
- Develop production-grade ML libraries, algorithms, and CLI tooling
- Implement automated workflows using CI/CD processes
- Collaborate with data scientists and engineers to improve the developer experience
- Flexible remote or hybrid setup
- Global, diverse team
- Supportive, collaborative atmosphere
- Private medical care
- Access to online learning and certifications
Join our mission to empower data-driven decision-making
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