11 hours ago
London, United KingdomStaff+
Responsibilities
- Define and lead the technical strategy for AI and machine learning systems supporting recommendations, matching, ranking, personalization, engagement, and member safety.
- Design, develop, and deploy production-grade ML models for high-traffic environments.
- Build and deploy production AI agents using foundation models, fine-tuned LLMs, sub-agents, tools, and MCP integrations.
- Architect end-to-end ML pipelines integrating Spark and Airflow with training, evaluation, deployment, and monitoring workflows.
- Define experimentation strategies using A/B testing, offline evaluation, and online measurement.
- Partner with Product, Engineering, Data Science, Analytics, and leadership to translate ambiguous member and business problems into scalable ML solutions.
- Set technical direction through influence, mentor senior individual contributors, and elevate ML engineering practices across the organization.
- Champion responsible AI practices covering fairness, transparency, privacy, and member safety.
Requirements
- Typically 10–15 years of relevant experience, with equivalent skills, scope, and impact accepted from alternative backgrounds.
- Deep hands-on experience designing, building, and deploying large-scale machine learning systems in production.
- Strong proficiency in Python and at least one major ML framework such as PyTorch or TensorFlow.
- Experience with recommendation systems, ranking, retrieval, personalization, or NLP, including model architecture, features, loss functions, evaluation, experimentation, and online versus offline trade-offs.
- Experience prompting and fine-tuning large language models and building production AI agents with modern agentic architectures and tooling.
- Experience designing scalable data and ML pipelines using Spark, Airflow, or comparable distributed data and orchestration systems.
- Ability to set technical direction and influence strategy as a senior individual contributor without direct authority.
- Ability to navigate ambiguous technical and product problems while balancing immediate delivery with longer-term architecture and ML strategy.
- Strong cross-functional collaboration, ownership, technical judgment, and AI fluency.
- Track record of mentoring and developing engineers and helping build inclusive, high-performing teams.
Tech Stack
Categories
About Bumble
Bumble Inc. builds consumer social apps for dating and friendship, including Bumble Date, BFF, and Badoo. The company runs a freemium business with subscriptions and in‑app purchases, and is publicly traded on Nasdaq as BMBL; founded in 2014 by Whitney Wolfe Herd, it is headquartered in Austin, Texas and serves a global user base.