Principal Machine Learning Engineer, Matching and Recommendations

About the role

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.

Key responsibilities

• 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.
• Mentor and elevate senior individual contributors, fostering a culture of excellence, curiosity, and continuous learning across the ML community.
• Champion responsible AI practices, ensuring fairness, transparency, and user safety are embedded into all machine learning systems.

Required profile

• Typically requires 10–15 years of experience, though alternative backgrounds demonstrating equivalent skills are welcome.
• Deep expertise in machine learning with hands‑on experience building and deploying large‑scale systems in production.
• Strong proficiency in Python and at least one major ML framework (e.g., PyTorch, TensorFlow).
• 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 without direct authority.
• Track record of mentoring and uplifting others, building inclusive high‑performing teams.

Required skills

• Python
• PyTorch
• TensorFlow
• Spark
• Airflow
• Large Language Models (LLMs)
• Recommendation systems
• Ranking models
• Natural Language Processing (NLP)