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.
As a Senior Software Engineer at Weights & Biases for our Sweeps product, you’ll build and maintain key features to allow users to effectively tune hyperparameters. You’ll work on the next generation of Sweeps, with a focus on allowing users to effectively distribute their hyperparameter tuning scripts across clusters and cloud infrastructure. You’ll also contribute to the development of Weights & Biases Launch, an execution layer being actively developed on the Weights & Biases platform. You will have the opportunity to design system architecture and APIs so users can easily send their workflows to the cloud, or local clusters.
Responsibilities:
- Design and implement features to help users build and tune the best models by leveraging large scale compute.
- Lead the maintenance of our existing Sweeps product and ensure a seamless transition to the next generation.
- Contribute to the design and implementation to an execution platform built on Weights & Biases.
- Focus on our end users and listen to customer feedback in order to deliver value.
Requirements:
- 4+ years of experience in software engineering
- Strong software engineering fundamentals and knowledge of at least 1 modern programming language (Python, Go, Typescript, GraphQL, etc)
- Strong empathy for ML practitioners with a keen interest in understanding and addressing their challenges.
- A desire to be self-driven and find the path to greatest impact.
- Nice to have: experience working with ML Engineers and building tools to allow them to easily connect with their compute.
Why join us?
- Top-tier machine learning teams rely on our tools for their daily work at companies including OpenAI, Toyota Research Institute, Lyft, Samsung, and Pandora.
- You'll never stop learning. This role gives you first-hand experience talking with leading researchers in the field, understanding their problems, and directly shaping the product direction.
- Our experienced founding team has successfully built and sold ML tools in the past at Figure Eight, and their deep knowledge of our industry, empathy for our users, and skillful management is driving W&B to success.
- Customers genuinely benefit from our tool. Here's a quote from Wojciech Zaremba, Cofounder and Robotics Lead, OpenAI: "W&B allows to scale up insights from a single researcher to the entire team, and from a single machine to hundreds of them."
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)
- Supplemental benefits may be available depending on your location
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].
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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.
