Lead Machine Learning Engineer

Introduction to the role & team
Bumble exists to create a world where all relationships are healthy and equitable, and our Machine Learning team plays a vital role in shaping how millions of people connect, build trust, and find belonging. In this role, you’ll operate at the intersection of product innovation and technical excellence, delivering intelligent systems that elevate both user experience and safety.

As a Lead Machine Learning Engineer, you’ll take ownership of complex, ambiguous problem spaces and drive end-to-end machine learning solutions that span modelling, systems, and product integration. You’ll champion our values of Courage and Excellence by making thoughtful technical decisions, challenging assumptions, and pushing for better outcomes.

AI is foundational to our future. You’ll not only build high-impact ML systems, but also embed best practices in how AI is applied across the team, helping others adopt scalable, responsible, and effective approaches.

• Lead the design and delivery of end-to-end ML systems powering recommendations, ranking, and personalization, driving measurable improvements in user outcomes

• Architect and optimise ML pipelines, integrating data processing, model training, evaluation, and deployment into scalable systems (e.g. Spark, Airflow) 

• Build and deploy advanced models using modern frameworks (e.g. PyTorch), ensuring robustness in high-scale production environments 

• Develop and apply LLM-based capabilities, including prompt design and fine-tuning approaches for production use cases 

• Drive experimentation strategy, including A/B testing and offline evaluation, to continuously improve performance and inform product decisions

• Partner cross-functionally with Product, Engineering, and Data teams, collaborating with purpose to translate business challenges into ML solutions

• Mentor and support other engineers, fostering a culture of Curiosity, ownership, and continuous improvement

• Typically requires 7–10 years of experience, though we welcome candidates with alternative backgrounds that demonstrate equivalent skills.

• Strong expertise in machine learning, with a track record of delivering end-to-end systems in production

• Proficiency in Python and ML frameworks (e.g. PyTorch, TensorFlow), with experience in areas such as recommendation systems, ranking, or NLP

• Experience designing and scaling ML pipelines and data systems (e.g. Spark, Airflow, or similar technologies)

• Hands-on experience with LLMs, including prompting, evaluation, and production integration 

• Demonstrated ability to take ownership of ambiguous problems and deliver impactful outcomes

• Strong collaboration skills, working cross-functionally and taking ownership of shared goals

• Solid AI fluency, with the ability to guide best practices in model development and responsible AI usage within a team