Backend/Data/Machine Learning Engineer Contractor

Salary Competitive

Do you want to join a fast-paced startup and work on the bleeding edge of recommendation systems, where your work immediately impacts the user experience for millions of users? We are looking for a Fullstack/Backend Engineer with 3+ years of coding experience.

What you will be building:

Recommendation systems that are guaranteed to always show relevant recommendations for any scenario and that are easy to maintain, deploy and improve.

We need someone who we can count on to:

🙋 Own: Improve our recommendation systems for new and existing customers, improve tooling to deploy, introspect and monitor our recommendation systems to constantly make them better.

đź’» Teach: What's possible and what's not possible? Tradeoffs between iteration speed and complexity of architecture. How to build a system that is easy to debug and that fails gracefully if there would be changes in the input data.

🎒 Learn: Our approach to recommendation systems, data engineering best practices, machine learning basics.

đźš´ Improve: Robustness, performance, and observability of our system, to delight the end-users of our product.

Desired skills and qualities

  • Deployed applications using cloud platforms or your own servers
  • Having worked in mature data engineering codebases
  • Experience in taking product decisions
  • Proficiency with cloud computing (AWS, GCP, or Azure)
  • Used Docker, Kubernetes, Argo, or similar

We expect you to:

  • Be proficient in Python
  • Have experience with data wrangling
  • Be comfortable with Linux/Unix CLI tools

Within 1 month we expect you to:

  • Get to know the team as well as learn from and collaborate on directing the product development forward
  • Understand the ins and outs of how our current recommendation system, data pipelines, and recommendation API works
  • Have been in customer calls understanding how customers perceive our product
  • Configure, optimize and measure the performance of newly onboarded e-commerce stores

Within 3 months we expect you to:

  • Significantly improve the quality of recommendations using more facets of data, impacting the user experience on many of our customers' e-commerce stores
  • Generalize our system, ensuring that recommendations for new stores are perfect from day zero with close to no fine-tuning necessary
  • Improve our codebase with robust automated tests and monitoring of recommendation's performance


Perks and benefits

This job comes with several perks and benefits

Free coffee / tea
Free coffee / tea

Get your caffeine fix to get you started and keep you going.

Flexible working hours
Flexible working hours

Time is precious. Make it count. Morning person or night owl, this job is for you.

Social gatherings
Social gatherings

Social gatherings and games; hang out with your colleagues.

Near public transit
Near public transit

Easy access and treehugger friendly workplace.

Equity package
Equity package

Want to be a partner? Look no further.

Free friday beers
Free friday beers

Friday is something special, let's enjoy a beer together.

See all 11 benefits

Working at is building AI-driven product recommendations. Increasing revenue for your store We use neural networks, computer vision and natural language processing to understand your products. This way we can start making high-quality recommendations immediately. Why do our recommendations work so well? Most recommendation systems use past transactions as their main source of data. We know better. Our system mimics the way humans understand products so that we can start showing relevant recommendations in your e-commerce store from day one.

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