Principal Machine Learning Engineer, Matching and Recommendations

Define and lead the technical strategy for AI and Machine Learning systems that power recommendations, ranking, and personalization across Bumble products, delivering measurable improvements in user engagement and safety

Design, develop, and deploy production-grade models using modern ML frameworks such as PyTorch , ensuring scalability and reliability in high-traffic environments 

Build and deploy production AI Agents using raw and fine-tuned foundational Large Language Models (LLMs), along with sub-agents, tools, and MCP integrations

Architect end-to-end ML pipelines, integrating data processing (e.g. Spark, Airflow) with model training, evaluation, and deployment workflows 

Drive experimentation frameworks, including A/B testing and offline evaluation, to continuously improve model performance and product outcomes

Partner cross-functionally with Product, Engineering, and Data leadership to translate business 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 the ML community

Take ownership of complex, ambiguous problem spaces, seeing initiatives through from insight to impact while adapting approaches with an agile mindset

Champion responsible AI practices, ensuring fairness, transparency, and user safety are embedded into all machine learning systems

Typically requires 10–15 years of experience, though we welcome candidates with alternative backgrounds that demonstrate equivalent skills.

Deep expertise in machine learning, with hands-on experience building and deploying large-scale systems in production environments

Strong proficiency in Python and at least one major ML framework (e.g. PyTorch, TensorFlow), with experience in areas such as recommendation systems, ranking models, or NLP 

Expertise in prompting and fine-tuning Large Language Models (LLMs) and building production AI Agents

Proven experience designing scalable data and ML pipelines using tools such as Spark, Airflow, or similar distributed systems 

Demonstrated ability to operate as a senior individual contributor, influencing technical strategy and decision-making without direct authority

Experience partnering effectively across functions, collaborating with purpose and taking ownership of outcomes in complex organisational environments

A track record of mentoring and uplifting others, role modelling Respect and Excellence while building inclusive, high-performing teams

Strong AI fluency, with the ability to independently design, evaluate, and optimise ML systems, and guide others in the responsible and effective application of AI