Software Engineer, Performance, Reliability, Observability, Phd, Early Career

Google Google · Big Tech · Warsaw, Poland

Software Engineer role focused on performance, reliability, and observability tools for Google Cloud control plane systems. The role involves analyzing VM performance, developing performance models, designing benchmarks, and exploring the use of machine learning for anomaly detection. While the core is engineering and performance analysis, there's an exploration component involving ML for anomaly detection.

What you'd actually do

  1. Conduct in-depth performance analysis of VMs, identifying critical bottlenecks, and developing performance models.
  2. Work closely with other engineers and researchers, communicating research findings and contributing to technical documentation.
  3. Design and conduct benchmarks to evaluate the effectiveness of proposed optimizations.
  4. Develop and patent novel optimization techniques.
  5. Share research results with the broader community through publications.

Skills

Required

  • PhD degree in Electrical Engineering, Computer Engineering, Computer Science, a related field, or equivalent practical experience.
  • Experience with software development in one or more programming languages (e.g., Python, C, C++, Java, JavaScript).

Nice to have

  • Experience with performance analysis tools and techniques (e.g., profiling, tracing).
  • Experience working with data structures or algorithms during coursework/projects, research, internships, or practical experience in school or work (e.g. open-source coding).
  • Proficiency in programming languages like C, C++, or Go.
  • Knowledge of operating systems and computer architecture.
  • Excellent research, problem-solving, and communication skills.

What the JD emphasized

  • PhD degree in Electrical Engineering, Computer Engineering, Computer Science, a related field, or equivalent practical experience.

Other signals

  • exploring options of using machine learning to automate anomaly detection
  • performance analysis of VMs
  • developing performance models
  • design and conduct benchmarks
  • develop and patent novel optimization techniques