About the role
Lead ML Engineer to design, build, and deploy end-to-end ML systems and LLM capabilities.
- •Bumble's Machine Learning team shapes how millions connect, build trust, and find belonging by delivering intelligent systems that elevate user experience and safety.
- •As a Lead Machine Learning Engineer, you will drive end-to-end ML solutions, from modeling to product integration, championing technical excellence and responsible AI practices.
- •Key Responsibilities Lead the design and delivery of end-to-end ML systems for recommendations, ranking, and personalization.
- •Architect and optimize scalable ML pipelines using technologies like Spark and Airflow.
- •Build and deploy advanced models using frameworks such as PyTorch, including LLM-based capabilities.
- •Drive experimentation strategy, including A/B testing, to improve performance and inform product decisions.
- •Partner cross-functionally with Product, Engineering, and Data teams to translate business challenges into ML solutions.
- •Requirements Typically requires 7-10 years of experience in machine learning with a track record of delivering end-to-end systems in production.
- •Proficiency in Python and ML frameworks like PyTorch, with experience in recommendation systems, ranking, or NLP.
- •Experience designing and scaling ML pipelines and data systems (e.g., Spark, Airflow).
Tech stack
PythonPyTorchSparkAirflowLLMsNLP
Match insights
Tech:Python, PyTorch, Spark, Airflow, LLMs
Level:Lead