Machine Learning Engineer (d/f/m)

Requirements

• University degree in Computer Science, Machine Learning, Data Science, or a related field
• 3+ years’ experience building and deploying production-grade machine learning models
• Strong software engineering mindset — ability to write clean, reusable, and scalable code in Python
• Experience integrating ML/AI models into production software systems
• Solid understanding of MLOps practices, CI/CD pipelines, and automated testing frameworks
• Hands-on experience with ML frameworks (e.g., TensorFlow, PyTorch, Hugging Face)

Nice to Haves

• Background in data science: comfort with experimentation, A/B testing, and measuring ROI/impact of ML projects (not just accuracy)
• Experience with NLP or generative AI techniques
• Familiarity with cloud-based ML infrastructure (AWS, Snowflake, SageMaker, etc.)

What you'll be doing

• Design, develop, and deploy robust machine learning and AI systems for a range of products and use cases, including generative AI
• Integrate ML and AI models into production systems, ensuring scalability, reliability, and maintainability
• Deploy and monitor machine learning models and systems, including CI/CD pipelines, automated testing, monitoring, and model versioning
• Leverage cloud platforms (AWS + Snowflake) and ML infrastructure (e.g., SageMaker, feature stores) for scalable deployment
• Collaborate with cross-functional teams (Product, Customer Experience, and other engineering teams) to deliver AI-driven features and insights
• Ensure all ML/AI solutions adhere to best practices in data privacy, security, and ethical standards
• Contribute to a culture of technical excellence, knowledge sharing, and continuous learning

Perks and Benefits

• Receive a competitive reward package – reevaluated each year – that includes salary, benefits, and pre-IPO equity
• Enjoy 28 days of paid vacation, plus an additional day after 2 and 4 years
• Make an impact on the environment and society with 1 (fully paid) Impact Day
• Receive generous family leave, child support, mental health support, and sabbatical opportunities
• On-site collaboration with 2 days a week in the London office, with flexibility to work remotely for the remaining days
• 20 Flex Days per year to work remotely from other locations
• Engage in team gatherings, cultural initiatives, and events like Summer Sessions and year-end celebrations
• Access to healthy snacks, drinks, and a weekly catered lunch