About Us

Proton.ai is revolutionizing wholesale distribution. Distributors sell nearly every physical good you come across. Key to the economy, they make up over 28% of GDP. But there’s a problem. Selling as a distributor is complicated. They carry hundreds of thousands of complicated products, making it impossible for sales teams to know what their customers need. Proton cuts through this complexity with machine learning. We provide a solution that modernizes distributors' sales efforts. And in doing so, we help distributors better serve their customers and grow.

Our company is in hyper-growth mode. We've had significant year-over-year revenue growth, and we just raised a $20M Series A backed by Felicis Ventures (investors in Twitch, Shopify, Opendoor, and many others) and Battery Ventures. Needless to say, it’s an exciting time to join the Proton.ai team.

The Role

At Proton, we're bringing cutting-edge machine learning to B2B distribution. By predicting what customers will buy, we're improving sales and efficiency, and driving growth. Of course, none of this matters without a great way to use our tool. We want to solve big problems with big solutions. Our goal is to offer deep, creative solutions to our users, not a hodgepodge of thoughtlessly assembled buttons and text fields.

As a machine learning engineer, you'll build the core machine technologies at the heart of our application. While we are pragmatic, we also want to push the envelope. Our machine learning team uses cutting-edge techniques when necessary. You'll go far deeper than basic linear regressions.

What You'll Do

• Work with our product management team to find translational applications of cutting-edge machine learning techniques to our user problems

• Collaborate with our infrastructure and security team to deliver machine learning insights securely, at speed, and at scale

• Research and learn about new techniques and model architectures

• Apply basic and complex machine learning models to power our core features

• Run and monitor field experiments to assess and refine your models

Experience that may be helpful

• Experimental design and hypothesis testing

• Familiarity with machine learning frameworks like TensorFlow or PyTorch

• Comfort reading, understanding, and applying machine learning research

• Familiarity with neural network architectures such as transformers and GANs for natural language processing, recommender systems, and classification problems

Benefits

This is a full-time, fully remote position, with occasional paid travel to in-person meetups. This job has base pay of $135,000 to $180,000 depending on level (United States; cost of living adjusted for other countries), plus equity, 401k with match, health benefits, 12 weeks' paid parental leave, a quarterly remote benefit stipend, and a take-what-you-need vacation policy (unlimited with a two-week minimum—no maximum).

We're a remote-first company and open to candidates anywhere in the world. While we try to accommodate employee's schedules, our business largely operates on East Coast hours.

Our Process

As you may have noticed, our hiring process is a little different. At Proton.ai, we assess candidates using an unbiased and thoughtful process. We ask questions directly related to the work you will be doing. Candidates enjoy our hiring process and tell us that the questions we ask make sense, plus they get to showcase their abilities.

Please bear in mind that we cannot hire from countries that have low World Justice Project rule of law scores. These countries include but are not limited to: China, Pakistan, Belarus, Iran, Nigeria, and Russia.

When answering our short answer questions, please be thoughtful. A throwaway answer will likely not get you to the next stage. You're welcome to consult external resources for any questions, however plagiarism will not be tolerated.

You can read more about that — and learn more about our engineering organization more generally — on our engineering blog.