Principal Software Engineer - Compute Infrastructure

Principal Staff Software Engineer - Compute Infrastructure - 15422

• Full-time
• Workplace Type:
  Hybrid
• Location:
  
  Mountain View, CA

Linked In is the world’s largest professional network, built to create economic opportunity for every member of the global workforce. Our products help people make powerful connections, discover exciting opportunities, build necessary skills, and gain valuable insights every day. We’re also committed to providing transformational opportunities for our own employees by investing in their growth. We aspire to create a culture that’s built on trust, care, inclusion, and fun – where everyone can succeed.

Join us to transform the way the world works.

At Linked In, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a Linked In office on select days, as determined by the business needs of the team.

As a Principal Staff Software Engineer of the Compute Infrastructure team at Linked In, you will play a crucial role in our ongoing efforts to re-architect our compute infrastructure stack. This is a high-profile, high-impact project that touches every aspect of our engineering organization. We are looking for professionals who have a proven track record of designing large-scale compute infrastructure and driving consensus.

In this role, you will design and implement solutions that enable Linked In to scale its compute infrastructure to meet the demands of a rapidly growing user base. This will involve working closely with a team of engineers to develop and operate solutions that are robust, scalable, and efficient. You will also need to work collaboratively with cross-functional teams and be comfortable operating in a fast-paced, dynamic environment.

If you are passionate about building the underlying technology that powers one of the world's most-used internet applications, and have the skills and experience to help us take our compute infrastructure to the next level, we want to hear from you. Apply now to join our team and help shape the future of Linked In.

• Directly contribute to Linked In’s Compute infrastructure strategy.
• Build and operate a platform that allocates hardware resources with necessary physical/logical distribution for fault tolerance and easy maintenance.
• Build and operate world class high performance scheduling/deployment solutions including some of the world's largest Kubernetes clusters to place stateless/stateful services, ML workloads and short running jobs efficiently.
• Help up-level and coach a large team of talented developers.

• 10+ years of industry experience in software design, development, and algorithm related solutions
• 10+ years of experience programming in object-oriented languages such as Java, Go, C/C++, Rust, Python
• 4+ years of experience as an architect, or technical leadership position
• BS/BA in Computer Science or related technical field or equivalent technical experience

• 15+ years of experience in software design, development, and algorithm related solutions
• 15+ years of programming experience in an object-oriented programming language such as Go, Java, C/C++, Rust
• 5+ years of experience in a technical leadership position
• 5+ years of experience building large-scale compute infrastructure, and distributed systems
• Demonstrated understanding of operating system fundamentals, container technologies, and systems knowledge.
• Experience building and operating cluster management solutions such as Kubernetes.
• Experience with IaaS systems and capacity management.
• Experience with networking and security principles.
• Experience in leading technical teams and mentoring other engineers

• Distributed Systems
• Technical Leadership

Linked In is committed to fair and equitable compensation practices. The pay range for this role is $226,000 to $369,000. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to skill set, depth of experience, certifications, and specific…