Machine Learning Engineer Intern

Machine Learning Engineer Intern

This job is no longer open
At Weights & Biases, our mission is to build the best developer tools for machine learning. Weights & Biases is a series C company with $200 million in funding and a rapidly growing user base. Our platform is an essential piece of the daily work for machine learning engineers, from academic research institutions like FAIR and UC Berkeley to massive enterprise teams including iRobot, OpenAI, Toyota Research Institute, Samsung, NVIDIA, Salesforce, Blue Cross Blue Shield, Lyft, and more.

You would be an intern on the Data Science team. On the Data Science team, we’re passionate about understanding and improving the customer experience of the platform and tools through measurement, analysis, modeling, development, and peer mentorship. 

This team gets to partner with product, engineering, and growth to ensure a virtuous cycle of customer feedback, product metrics, product development, and experience optimization.

In this role, you will build machine learning models and applications using our suite of MLOps tools. You will partner with the Data Science, Data Engineering, and Product Engineering teams to build compelling machine learning projects, and work with the Growth team to communicate and popularize that work.

This role is Remote friendly and we have an office in Downtown San Francisco. This role can range from 2-4 months depending on applicant's schedule.

What you'll achieve in this role:

    • Brainstorm with Product Managers to instrument our products to guide new tools and features for all data scientists.
    • Pair directly with our Engineers to work with alpha features and provide feedback from the ML practitioner mindset.
    • Build models, apps, and pipelines to expand the domains of our application areas..
    • Serve as a subject matter expert from an area of machine learning that you wish to teach the team and the greater ML community.

About You:

    • Practical experience with an area of Machine learning; especially interested in Recommendation Systems, AdTech, Time-series, Multi-modal, geometric DL, or Statistical simulation.
    • Knowledge of python and the relevant ML frameworks in your domain–pytorch, TF, JAX, etc.
    • Excitement for MLOps and the Deep Learning toolchains.
    • History of writing easy-to-follow code and effective documentation for your projects.
    • Ability to clearly communicate your ideas to folks across a range of backgrounds and levels of technical knowledge.

Why Join Us

    • Top-tier machine learning teams love and rely on our tools for their daily work at companies including Nvidia, OpenAI, Toyota Research Institute, Lyft, Samsung, and Pandora.
    • We have extensive experience working with companies to turn machine learning research projects into scalable, real-world deployments. We’ve watched hundreds of teams struggle to deploy machine learning models successfully, and the same problems show up repeatedly. Machine learning has created a fundamentally new kind of programming, requiring a fundamentally new set of developer tools. We created Weights & Biases to provide that missing toolkit.
    • Our user base is growing rapidly.
    • We have raised significant capital, but the team is still small and there is the room and resources to make a big impact.
    • Here's a quote from Wojciech Zaremba, Cofounder and Robotics Lead, OpenAI: "W&B allows us to scale up insights from a single researcher to the entire team, and from a single machine to hundreds of them."
    • Our data stack: Python, BigQuery, Mode, Segment, and the DL zoo
    • You’ll be one of the first data engineers to be doing ML for the MLOps space; meta machine learning on the world’s DL experimentation data.
W&B is free for individuals and academic users. We'd love it if you created a project and made a report in W&B on any topic that interests you. You can find inspiration and examples of reports at
We are looking for individuals located in the United States to cover the pacific time zone and eastern time zone.

We encourage you to apply even if your experience doesn't perfectly align with the job description. Team members who love to learn and collaborate in an inclusive environment will flourish here. 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

This job is no longer open
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