Role overview

Machine Learning Engineer

Requirements and responsibilities

Readable role content extracted into sections for faster review.

In this role you will...

  • Develop & Scale ML Models: Build, train, and deploy high-performance machine learning prediction models optimized for real-time adtech environments.
  • Own the Full ML Path: Take models from raw data and feature definitions through training, evaluation, and online serving. Feature engineering and online/offline consistency matter as much as modelling skill.
  • Optimize the Bidding Engine: Design and refine complex bidding algorithms, orchestrating how multiple models interact together in milliseconds to make optimal final bidding decisions.
  • Run & Analyze Experiments: Design, execute, and evaluate both offline simulations and online A/B tests to measure and analyze algorithmic impact on core business metrics.
  • Collaborate Cross-Functionally: Step outside the traditional ML silo to collaborate with engineering and product partners, adapting quickly to diverse technical challenges.
  • Augment Your Workflow: Actively integrate new AI tools and coding agents into your daily process to maximize throughput, experiment velocity, and code quality.

You will be a great fit if...

  • Technical Stack: You have strong proficiency in Python and TensorFlow for building ML models, and comfortable reading Go to navigate our online serving services, this would be easy to pick up if you already know Python.
  • Growth Mindset: Beyond core ML, our work touches a range of disciplines like reinforcement learning, control engineering, mathematical optimisation, and causal inference, to name a few. If you already have depth in any of these, great; if not, there's plenty of interesting territory to explore alongside the core ML work.
  • Healthy Skepticism & Pragmatism: You don't just build complex models because they are trendy; you use data-driven analysis to find the most pragmatic solution to the problem at hand.
  • Ownership Mindset: You are adaptable and thrive when given the autonomy to take a project from early-stage experimentation all the way through to production.
  • AI-Forward: You possess a genuine curiosity about the evolution of AI and are enthusiastic about leveraging AI coding tools to optimize your engineering workflows.

Our promise

  • Unlimited vacation days - for real. We give you the freedom to figure out the most productive work-life balance for you
  • A truly modern place to work: work from home, from our brand new office in Berlin, or remotely - your work environment is yours to design
  • Generous remuneration package including virtual shares, a dedicated education budget
  • End of the year bonus determined by company performance
  • Enrol in our Short Term Assignment (STA) program and travel to our offices around the globe for up to a month - subject to eligibility and internal policy
  • Comfortable work setup - laptop, phone, screen(s), standing desk etc.
  • Support for your setup while working from home
  • Wellness benefits such as sports memberships, Nilo Health subscription and internet reimbursements
  • Company events including breakfast twice a week, team lunches, birthday and milestone celebrations, quarterly team events and company-wide parties & trips
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Browse stack
FocusMachine Learning EngineerRole area
Seniority signalSeniorCandidate level
StackPythonPrimary skills
Location1 accepted countryEligibility

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