Machine Learning Engineer responsible for implementing and maintaining data science models in bpx’s machine learning studio. Bridging data science and computational needs to achieve business outcomes.
About the role
- Senior MLOps Engineer developing machine learning tools and pipelines for JetBrains. Aiming to streamline MLOps and improve AI productivity for innovative teams.
Responsibilities
- Build tools, automation, and workflows to simplify infrastructure-heavy tasks, empowering AI teams to focus on experimentation and solving core challenges.
- Develop robust monitoring, logging, and tracing systems to ensure the performance and reproducibility of ML workflows in production.
- Design, implement, and maintain end-to-end machine learning pipelines to enable the seamless development, training, and deployment of ML models and intelligent agents.
- Work with large-scale distributed systems, including GPU clusters, to support training, fine-tuning, and evaluation of ML models.
- Collaborate with product and development teams to transform high-level goals into concrete, scalable, and maintainable systems.
- Optimize workflows for reproducibility, scalability, and cost-efficiency while keeping ML teams productive and focused on innovation.
Requirements
- Hands-on experience with modern MLOps tooling, including Kubernetes
- A solid understanding of the ML lifecycle from idea to the customer-facing application
- The ability to own projects end to end, starting from a high-level problem or product pain point and overseeing it through the design, experimentation, implementation, and iteration phases
- A customer-centric mindset – you care about how ML engineers are actually working and can translate their needs into actionable, scalable, and maintainable architectural decisions
- Experience with modern CI/CD systems, like GitHub Actions or JetBrains TeamCity
- At least three years of Python experience writing clean, maintainable code in modern ML codebases.
Benefits
- Health insurance
- Retirement plans
- Paid time off
- Flexible work arrangements
- Professional development
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
No Education Requirement
Tech skills
Location requirements
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