Software Engineer, Weights & Biases
Sweeps
$146-203k
+ Equity
MLOps platform for developers
Open for applications
MLOps platform for developers
201-500 employees
Open for applications
$146-203k
+ Equity
201-500 employees
Company mission
Weights & Biases's mission is to build the best tools for machine learning.
Role
Who you are
- 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
What the job involves
- As the software engineer in charge of Weights & Biases 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
- 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
Our take
Weights & Biases (W&B) builds development tools for machine learning, helping businesses to create and use deep learning models. In order for deep learning to work, it’s necessary for companies to be able to monitor how the models are behaving as they are trained. With over 200,000 customers, W&B has differentiated itself from its competitors such as IBM Watson Studio and Valohai by focusing exclusively on machine learning practitioners and not on sales aspects of the technology, and by its competitive pricing.
The company has also launched a product to help different parties collaborate on machine learning models. This is geared at researchers, reducing the need for them to rerun their training examples repeatedly. Over time, this will help to move machine learning technology forward. What's more, W&B's technology is free for personal and academic use, which has fueled adoption enormously, and it is now being used by research institutions such as UC Berkeley and enterpise companies like Samsung and Salesforce.
The dependence on machine learning is growing as more and more companies begin to use artificial intelligence to handle business tasks, so demand for this sort of software is rising. Having raised substantial funding, W&B is moving to futher develop its product, grow its team and increase its marketing reach.
Steph
Company Specialist
Insights
Company
Funding (last 2 of 5 rounds)
Aug 2023
$50m
LATE VC
Oct 2021
$135m
SERIES C
Total funding: $250m
Company benefits
- 🏝️ Unlimited vacation time
- 🩺 100% Medical, Dental, and Vision for employees and Family Coverage
- 🏠 Remote first culture with in-office flexibility in San Francisco
- 💵 $500 home office budget with new high-powered laptop
- 🥇 Truly competitive salary and equity
- 🚼 12 weeks of Parental leave
- 📈 401(k)
Company values
- We're building a culture where people love coming to work to build cool things and collaborate with other smart people
- It’s important to us that everyone feels comfortable being themselves and being honest with each other, and all of us take responsibility for making our customers successful
- We love to work with people who are driven, kind and proactive
- We care about diversity and if you are part of an underrepresented minority, we especially encourage you to apply to work here
- We are contributing to responsible AI with tools for transparency and reproducibility in model development and deployment
Company HQ
SoMa, San Francisco, CA
Articles
Founders
Chris Van Pelt
(CISO)Earned a BA in Computer Science at Hope College. Previously Lead Engineer and Founder of Figure Eight (acquired by Appen).
Lukas Biewald
(CEO)Earned a BS in Mathematics and MS in Computer Science from Stanford University. Previously Research Scientist and Founder, CEO of Figure Eight (acquired by Appen).
Shawn Lewis
(CTO)Earned his BS in Computer Engineering at Virginia Tech. Previously Engineer at Google and Founder at Beep Networks.
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