Principal Machine Learning Engineer, Matching & Recommendations

Machine Learning sits at the heart of our mission, helping us understand what makes a meaningful connection and powering the matching, recommendation and personalisation experiences that bring people together.

As our Principal Machine Learning Engineer, Matching & Recommendations, you’ll help define the technical and ML strategy behind the next generation of Bumble’s recommendation systems. You’ll remain hands-on while tackling complex problems across retrieval, ranking, personalisation, experimentation and two-sided marketplace optimisation, partnering across Engineering, Product, Data Science and Analytics to turn ambiguous member problems into scalable ML solutions. You’ll lead through technical influence, raise the bar for ML engineering across the organisation, and help us build systems that optimise not simply for engagement, but for better connections and meaningful member outcomes.

What you'll do

• Define and lead the technical strategy for AI and Machine Learning systems that power recommendations, matching, ranking and personalisation across Bumble products, delivering measurable improvements in member outcomes, engagement and safety.
• Design, develop and deploy production-grade models using modern ML frameworks such as PyTorch, ensuring scalability, reliability and performance in high-traffic environments.
• Build and deploy production AI agents using foundation models and fine-tuned Large Language Models (LLMs), alongside sub-agents, tools and MCP integrations.
• Architect end-to-end ML pipelines, integrating large-scale data processing technologies such as Spark and Airflow with model training, evaluation, deployment and monitoring workflows.
• Define and evolve experimentation strategies, including A/B testing, offline evaluation and online measurement, to continuously improve model performance and product outcomes.
• Partner cross-functionally with Product, Engineering and Data leadership to translate complex business and member challenges into impactful ML solutions, collaborating with purpose and influencing at senior levels.
• Mentor and elevate senior individual contributors, fostering a culture of Excellence, Curiosity and continuous learning across Bumble’s ML community.
• Take ownership of complex and ambiguous problem spaces, seeing initiatives through from insight to measurable impact whilst adapting approaches as new information emerges.
• Champion responsible AI practices, ensuring fairness, transparency, privacy and member safety are considered throughout the design and operation of Machine Learning systems.

About you

• Typically, you will have 10–15 years of relevant experience, although we welcome candidates with alternative backgrounds who can demonstrate equivalent skills, scope and impact.
• You have deep expertise in Machine Learning, with significant hands-on experience designing, building and deploying large-scale ML systems in production environments.
• You have strong proficiency in Python and at least one major ML framework, such as PyTorch or TensorFlow, with experience in areas such as recommendation systems, ranking, retrieval, personalisation or NLP.
• You understand modern recommendation-system approaches and can reason deeply about model architecture, features, loss functions, evaluation methodology, experimentation and the trade-offs between offline performance and online outcomes.
• You have experience prompting and fine-tuning Large Language Models (LLMs) and building production AI agents using modern agentic architectures and tooling.
• You have proven experience designing scalable data and ML pipelines using technologies such as Spark, Airflow, or comparable distributed data and orchestration systems.
• You have demonstrated the ability to operate as a senior individual contributor, setting technical direction and influencing strategy across teams without relying on direct authority.
• You are comfortable navigating highly ambiguous technical and product problems, balancing immediate delivery with longer-term architectural and ML strategy.
• You partner effectively across functions, collaborating with purpose and taking ownership of outcomes in complex organisational environments.
• You have a track record of mentoring and developing other engineers, role-modelling Respect and Excellence whilst helping build inclusive, high-performing teams.
• You bring strong AI fluency and technical judgement, with the ability to independently design, evaluate and optimise ML systems whilst guiding others in the responsible and effective application of AI.