Staff Software Engineer, Metrics - US (Remote)

As a Staff Software Engineer, Metrics at Weights & Biases, you'll be instrumental in designing and implementing scalable infrastructure tailored to customer needs. You'll lead the maintenance of existing services, ensuring their performance and reliability, while also participating in team-wide rotations to address customer support issues. Additionally, you'll communicate effectively with stakeholders and mentor junior engineers to foster their growth.

To qualify for the Staff Software Engineer, Metrics position at Weights & Biases, candidates should possess 8+ years of software engineering experience, particularly in data platforms or distributed systems. Proficiency in at least one modern programming language, such as Python, Go, or Typescript, along with experience designing and scaling customer-facing APIs in production, is essential. Familiarity with tools like Kubernetes and Terraform, as well as major cloud providers, is also required.

Weights & Biases is committed to the professional development of its Staff Software Engineers by fostering an inclusive and collaborative work environment. You'll have the opportunity to mentor junior engineers, enabling them to grow while also contributing to architecture improvements and strategic projects that align with your technical expertise and interests.

The estimated annual salary for the Staff Software Engineer, Metrics at Weights & Biases ranges from $210,000 to $290,000. This competitive compensation is informed by your skills, qualifications, and experience, along with the responsibilities associated with the role.

Weights & Biases offers an array of benefits for its Staff Software Engineers, including flexible time off, comprehensive medical, dental, and vision coverage for employees and their families, and a home office budget. Additionally, you'll benefit from a competitive salary and equity options, parental leave, and a 401(k) plan. We also prioritize your overall well-being through supplemental benefits depending on your location.

It's essential to articulate your background in software engineering and highlight specific projects related to data platforms or distributed systems. Discuss the technologies you've utilized, such as MySQL or Kafka, and any scaling challenges you faced, showcasing your problem-solving capabilities.

Mention the modern programming languages you are skilled in, such as Python or Go, and provide examples of how you've used them in developing customer-facing APIs or other projects. Illustrate your ability to write efficient, maintainable code that meets user needs.

When discussing your approach to scalable infrastructure design, emphasize the importance of understanding user requirements and system performance. Provide examples of how you've implemented scalable solutions in previous roles, taking into account factors like cost-effectiveness and data management.

Share your methods for service maintenance, focusing on monitoring, identifying performance issues, and implementing improvements. Mention any tools or processes you've found effective in maintaining service reliability over time.

In your answer, illustrate a specific incident where you played a key role in resolving a customer support issue or site outage. Detail the steps you took to diagnose the problem and implement a solution while communicating with all stakeholders.

Discuss your thought process in balancing short-term goals and long-term infrastructure enhancements. Provide examples of how you've navigated competing priorities and ensured alignment with broader company goals, demonstrating your strategic thinking.

Describe specific experiences mentoring junior engineers, focusing on your approach to fostering their development and ensuring they feel supported. Highlight any successes resulting from your mentorship that contributed to the team’s overall effectiveness.

Talk about your hands-on experience with cloud platforms like AWS or GCP, emphasizing how you've directly used Kubernetes and Terraform in your projects. Share specific scenarios where these tools significantly enhanced project deployment or management.

Emphasize your collaboration skills and openness to feedback. Provide examples of how you've accepted constructive criticism from product management or other teams and how it positively influenced your work or project outcomes.

Share your insights on the evolution of AI development and how platforms like Weights & Biases can support this growth. Discuss the significance of having robust tools for experiment tracking and analytics in shaping the future of machine learning.