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Bumble is seeking a Principal Machine Learning Engineer to lead the technical and ML strategy for recommendation systems, ranking, and personalization across its dating and friendship platforms. This is a hands-on senior role where you'll define strategy while remaining deeply involved in complex ML engineering work.
You will design and deploy production-grade models using modern frameworks like PyTorch, architect end-to-end ML pipelines integrating data processing (Spark, Airflow) with model training and deployment, and build production AI Agents using fine-tuned LLMs with sub-agents and tool integrations. You'll drive experimentation frameworks including A/B testing and offline evaluation to continuously improve model performance and user outcomes. A key part of the role is partnering cross-functionally with Product, Engineering, and Data leadership to translate business challenges into scalable ML solutions, while mentoring senior individual contributors and fostering a culture of excellence and continuous learning.
You'll take ownership of complex, ambiguous problem spaces—seeing initiatives through from insight to impact—while championing responsible AI practices to ensure fairness, transparency, and user safety are embedded in all systems. The role emphasizes technical influence and raising the bar for ML engineering across the organization, with a focus on optimizing not just for engagement but for better connections and meaningful member outcomes.
Bumble Inc. is the parent company of Bumble Date, BFF, and Badoo, connecting people across dating and friendship. Founded in 2014 by Whitney Wolfe Herd, Bumble was built with women at the center and pioneered equitable relationship-building platforms.
Requirements:
- Typically 10–15 years of experience in machine learning, though alternative backgrounds demonstrating equivalent skills are welcome
- Deep expertise in building and deploying large-scale ML systems in production environments
- Strong proficiency in Python and at least one major ML framework (PyTorch, TensorFlow, or similar)
- Hands-on experience with 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 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 and taking ownership of outcomes in complex organizational environments
- Track record of mentoring and uplifting others, building inclusive, high-performing teams
- Strong AI fluency with the ability to independently design, evaluate, and optimize ML systems
