Principal Machine Learning Engineer, Matching and Recommendations

At Bumble, we’re building the Love Company — a place where healthy, equitable relationships and friendships can start and grow. Machine Learning sits at the heart of that mission, helping us understand what makes a meaningful connection and powering the matching, recommendation, and personalization 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, personalization, experimentation, and two-sided marketplace optimization
, 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 organization, and help us build systems that optimize not simply for engagement, but for better connections and meaningful member outcomes.

• 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, Tensor Flow), 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 organizational environments
• A track record of mentoring and uplifting others, role modeling Respect and Excellence while building inclusive, high-performing teams
• Strong AI fluency, with the ability to independently design, evaluate, and optimize ML systems, and guide others in the responsible and effective…