Principal Machine Learning Engineer, Matching and Recommendations

What you'll do

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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

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

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

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

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

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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

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Mentor and elevate senior individual contributors, fostering a culture of Excellence, Curiosity, and continuous learning across the ML community

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

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

About You

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

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

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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

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

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

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

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

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