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.
In this role you’ll lead efforts to scale our metrics and storage engines to the needs of our rapidly growing userbase. You’ll be instrumental in the evolution of our platform as we grow to ingest and query petabytes of data by making technical decisions that maximize the performance, reliability, and cost-effectiveness of our systems.
Responsibilities:
- Scale a platform trusted by leaders in the ML industry to ingest and query terabytes of data daily
- Define the architecture for our next-generation data ingestion and querying systems to achieve high performance and reliability
- Advise and educate development teams on how to build and operate scalable, performant services
Requirements:
- 5+ years of software development experience working on high scale customer-facing APIs
- Experience with systems such as MySQL, Postgres, Bigtable, or Kafka
- Strong understanding of at least one higher-level language including Go, Python or TypeScript
- A demonstrated record of leading complex projects to success, from planning to execution
- A proven ability to mentor and grow junior engineers
- Excellent communication skills and an ability to explain deeply technical concepts simply
- A willingness to dive into and debug issues at any layer of the tech stack, from the application layer to the network
- A demonstrated ability to think critically under pressure
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."
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.
