Machine Learning Engineer

At Batelle, we’re solving sleep for the next generation.

What we’re doing. Our goal is to help parents navigate their children's sleep challenges. We are developing a chat-first solution built on top of Large Language Models (LLMs) to guide parents each step of the way.

Why we’re doing it. A child’s sleep plays an integral role in their development and in the parents' overall well-being, yet parents everywhere struggle to get their children to sleep at night. Traditional sleep training methods are not only based on outdated research, but also have a one-size-fits-all approach, leaving parents feeling lost, and failing to get the results they want.

So far we’ve… Developed our own data-backed sleep training method, that’s tailored to each individual family. Since the start, we built our solution around a chat interface. We believe that chat is the most flexible medium to teach parents according to their needs and provide in-the-moment assistance to tackle challenges as they arise.

What’s next? We’ve already helped over 3,000 families achieve their sleep goals through our team of sleep specialists. We’re now taking those learnings and scaling them to help the millions of parents internationally who are up much later than they want to be.

Requirements

We're looking for a Machine Learning Engineer to join our core product team.

You’ll be

• Working on a broad range of Machine Learning problems, mainly around Large Language Models.
• Developing internal tools in collaboration with our sleep specialists to create and manage content.
• Shipping to production daily.
• Analyzing logs and metrics to understand user behavior.
• Reporting to our CTO, and working closely with our VP of Product and the mobile engineering team.

We think you'll be a great fit if you

• Have a background in Machine Learning and are comfortable working with a range of models. You choose the tool that fits the problem (GLMs, XGBoost, convex optimization, etc..). Neural networks isn't the only tool in your toolbox. You also understand how the models work, not just how to use the library (although hopefully you default to using pre-existing implementations ;) ).
• Know how to turn a business problem into a modeling objective, and you have significant experience debugging Machine Learning models.
• You're experienced in python and aren't afraid to get your hands dirty with Javascript/Typescript (experience not required).
• You’re motivated by building a great product and having an impact on users
• You thrive in a fast-paced startup environment: You take an MVP approach, releasing small changes regularly so you can get fast feedback. You’re comfortable working with ambiguity, and don’t let perfect be the enemy of the good.
• Clean and readable code is important to you: You take to heart that people will spend more time reading your code than you’ll spend writing it.
• You take ownership, have initiative, and are able to work on large projects independently.

Our tech stack

We’re a small team and choose tools that allow us to be nimble. For Machine Learning applications we use Python. Other than that we're primarily TypeScript based, using React Native for our mobile app, Node.js/Firebase for our web-backend, and Vue.js for our web-frontend.

Benefits

What we can offer you

• Competitive salary and significant options in the business.
• Opportunity to be an early engineer at a fast-growing startup.
• Fully remote team - you can be based anywhere in Europe between GMT and GMT + 3 timezones.
• $1000 stipend to set up your home office + $200 / month co-working budget.
• 20 days paid leave + your country’s national holidays.
• Yearly learning & development budget - learning and curiosity are among our team values!
• Engineering team offsite twice per year.

Why you’ll love it here

• You’re solving a real-world problem with life-changing impact on families — check out our TrustPilot.
• You’ll work with an incredibly talented, diverse, and fun-loving team across Europe.
• You’ll be learning first-hand how to develop products around the latest in LLMs. — Batelle’s in that sweet spot overlap of the Venn diagram between working on exciting new tech and solving real problems.

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