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Piotr Niedzwiedz

CEO/CTO & founder of neptune.ai | Talking about internal ML platforms, MLOps and LLMOps

Piotr Niedzwiedz is the CEO of Neptune.ai, focusing on the product side of things while overseeing the company's operations.

His journey into machine learning began with a background in software engineering, combined with a passion for math and programming from a young age.

With a strong foundation in algorithmics and programming competitions during high school, Piotr pursued a Computer Science and Mathematics program in Poland, which now specializes in machine learning.

Having interned at tech giants like Facebook and Google, Piotr opted to venture beyond being a FAANG engineer. He co-founded Codilime, a software consultancy, and later Deepsense.ai, a machine learning consultancy, where he served as the CTO.

His transition to the ML space revealed a need for better experimentation practices and tools, leading to the creation of Neptune.ai after identifying a gap in experiment management solutions.

Piotr holds a Master of Science in Computer Science, along with studies in Mathematics and a Bachelor's degree in Computer Science from the University of Warsaw.

His professional experience includes roles such as CEO/CTO & Founder at Neptune Labs, Inc., Co-founder & CTO at deepsense.ai, and Software Engineer Intern at both Facebook and Google.

Highlights

May 27 · linkedin

What can be worse than developing a product no one uses?

I asked Stefan Krawczyk how they approach post-deployment, encourage the use of the new product. And here are some lessons from Stitch Fix:

𝐈𝐝𝐞𝐧𝐭𝐢𝐟𝐲 𝐚 𝐮𝐬𝐞 𝐜𝐚𝐬𝐞: Start by finding someone with a genuine need who is willing to partner with you to improve the product.

𝐁𝐫𝐨𝐚𝐝𝐞𝐧 𝐚𝐰𝐚𝐫𝐞𝐧𝐞𝐬𝐬: Once you've established a use case, think about how to increase awareness of the product.

𝐌𝐚𝐢𝐧𝐭𝐚𝐢𝐧 𝐡𝐢𝐠𝐡-𝐟𝐢𝐝𝐞𝐥𝐢𝐭𝐲 𝐝𝐨𝐜𝐮𝐦𝐞𝐧𝐭𝐚𝐭𝐢𝐨𝐧: Ensure you have regularly updated documentation available for users.

𝐈𝐦𝐩𝐥𝐞𝐦𝐞𝐧𝐭 𝐞𝐟𝐟𝐞𝐜𝐭𝐢𝐯𝐞 𝐭𝐞𝐥𝐞𝐦𝐞𝐭𝐫𝐲: Use telemetry (like Slack alerts) to quickly access information about errors or challenges users face.

𝐓𝐢𝐦𝐢𝐧𝐠 𝐢𝐬 𝐜𝐫𝐮𝐜𝐢𝐚𝐥: Starting at the right time is the biggest challenge. But timing your engagement and support efforts also can make a significant difference.

See the full episode: https://buff.ly/3UVPviz

#ML #DataScience #MLPlatform

What can be worse than developing a product no one uses?

I asked Stefan Krawczyk how they approach
Apr 26 · linkedin

Navigating the complexities of product management without dedicated managers is tough.

It taught Stefan Krawczyk, co-founder at DAGWorks Inc., to double as his own by:

  • Prioritizing business value
  • Mastering time management

From my experience of running product and engineering at neptune.ai, another challenge is the perception of tech-savvy engineers — they often blend the problem (wrapped as a feature request) with the solution.

See the difference? The feature request is not always the optimal solution for the problem your customers are facing.

  • Spot the problem first!

See the full episode: https://buff.ly/3DKnLp4

#MLOps #productmanagement #machinelearning

Piotr Niedzwiedz
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Location

Warsaw, Mazowieckie, Poland