Junior SRE

Requirements

• A degree (BSc or MSc) in Computer Science, Engineering, Applied Mathematics, or a related field, or equivalent practical experience.
• Strong foundations in computer science (e.g. algorithms, data structures, operating systems, distributed systems).
• Experience developing software in at least one language such as Python, C++, or Rust.
• Familiarity with writing, testing, and maintaining production-quality code.
• Ability to reason clearly about technical problems and communicate effectively with teammates.
• Interest in infrastructure, performance, and large-scale systems.
• Exposure to machine learning workflows, data engineering, or ML platforms.
• Experience working in Linux environments.
• Introductory knowledge of distributed systems, HPC, or cloud platforms for CPU and GPU workloads.
• Experience with profiling, benchmarking, or performance analysis.

Nice to Have

• Familiarity with CUDA or other GPU development frameworks.

What You'll Be Doing

• Design, implement, and maintain data pipelines for machine learning training and inference.
• Develop and improve workflow orchestration and infrastructure components (e.g. scheduling, resource allocation, data movement, filesystems).
• Analyze and improve performance and scalability of systems and critical code paths.
• Improve the reliability, observability, and usability of ML or HPC platforms.
• Collaborate with quantitative researchers and developers to understand requirements and translate them into robust technical solutions.
• The opportunity to work on production-grade ML and HPC infrastructure at scale.

Perks and Benefits

• Strong mentorship and technical guidance from experienced engineers.
• Gradual ownership of meaningful systems and components.
• Exposure to real-world performance, scalability, and reliability challenges.
• Close collaboration with quantitative researchers and developers.