At Weights & Biases, our mission is to build the best tools for AI developers. We founded our company on the insight that while there were excellent tools for developers to build better code, there were no similarly great tools to help ML practitioners build better models. Starting with our first experiment tracking product, we have since expanded our solution into a comprehensive AI developer platform for organizations focused on building their own deep learning models and generative AI applications.
Weights & Biases is a Series C company with $250M in funding and over 200 employees. We proudly serve over 1,000 customers and more than 30 foundation model builders including customers such as OpenAI, NVIDIA, Microsoft, and Toyota.
Reporting to the Engineering Manager for Workspaces, this Senior/Staff Software Engineer will lead the technical planning, implementation, and delivery of key features within the Models product—our central hub for experiment tracking and visualization. In this role, you'll work closely with product managers, designers, platform engineers, and fellow engineers to scale the performance & reliability of the application while meeting the growing demands of ML teams.
Responsibilities:
- Build out features for our Models product that allow ML engineers to track, visualize and analyze data for their experiments.
- Collaborate with a team of 2-4 Software Engineers to navigate complex technical challenges, elevating the team’s ability to design robust APIs, and implement backend changes, and think critically about scalability.
- Collaborate with product and design to translate complex user requirements into elegant technical implementations.
- Identify and refactor areas of technical debt, improving code maintainability, developer productivity and application performance.
- Work cross-functionally to establish engineering patterns and best practices that balance immediate feature delivery with long-term platform health.
- Break down work into iterative, incremental changes, leveraging agile methodologies to ship fast and gather user feedback early and often.
Requirements:
- 5+ years of software engineering experience, with 3+ years leading significant technical initiatives or architectural changes.
- Strong proficiency in Python.
- Proficiency in at least one compiled language (C++, C, C#, Go), with Go experience being a significant bonus.
- Experience with GraphQL APIs, query optimization, and data fetching strategies.
- Experience with React & Typescript.
- Demonstrated success in improving the performance and maintainability of complex web applications.
- Comfort diving into complex systems to diagnose pain points and solve difficult bugs across the full stack.
- Exceptional communication skills with ability to explain complex technical concepts to various audiences.
Benefits:
- Our Benefits
- 🏝️ Flexible time off
- 🩺 Medical, Dental, and Vision for employees and Family Coverage
- 🏠 Remote first culture with in-office flexibility in San Francisco
- 💵 Home office budget with a new high-powered laptop
- 🥇 Truly competitive salary and equity
- 🚼 12 weeks of Parental leave (U.S. specific)
- 📈 401(k) (U.S. specific)
We encourage you to apply even if your experience doesn't perfectly align with the job description as we seek out diverse and creative perspectives. Team members who love to learn and collaborate in an inclusive environment will flourish with us. We are an equal opportunity employer and do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. If you need additional accommodations to feel comfortable during your interview process, reach out at [email protected].
#LI-Remote
Top Skills
What We Do
Weights & Biases helps machine learning teams build better models faster. With a few lines of code, practitioners can instantly debug, compare and reproduce their models — architecture, hyperparameters, git commits, model weights, GPU usage, and even datasets and predictions — and collaborate with their teammates.
