Staff Machine Learning Engineer

Introduction to the role & team  At Bumble, our mission is to create a world where all relationships are healthy and equitable - and at the heart of that mission is our ability to build intelligent, trustworthy systems at scale. As part of the Machine Learning team, you’ll play a critical role in shaping how AI powers connection, safety, and personalisation across our products. As a Staff Machine Learning Engineer, you’ll operate as a highly autonomous technical leader, owning large, complex problem spaces and driving end-to-end machine learning systems that influence product direction and user outcomes. You’ll role model our values of Excellence and Curiosity by elevating technical standards, mentoring others, and continuously pushing the boundaries of what’s possible with AI. AI is central to how we evolve. In this role, you’ll not only build advanced ML systems, but also shape how they are designed, scaled, and responsibly applied across teams - embedding best practices that enable long-term impact. About Us Bumble Inc. is the parent company of Bumble Date, BFF, and Badoo. The Bumble platform enables people to build healthy and equitable relationships, through Kind Connections. Founded by Whitney Wolfe Herd in 2014, Bumble was one of the first dating apps built with women at the center and connects people across dating (Bumble Date) and friendship (BFF). BFF is a friendship app where people in all stages of life can meet people nearby and create meaningful platonic connections and community based on shared interests. Badoo, which was founded in 2006, is one of the pioneers of web and mobile dating products. AI Fluency AI is important to us. We’re excited by people who are curious and experimental, and who think thoughtfully about how AI can amplify their impact and outcomes. We encourage you to use AI responsibly as you prepare your application. Please don’t use it to fabricate experiences or answer questions live in interviews. We care deeply about authenticity and want to understand your real skills, judgment and voice, because building a meaningful, genuine connection with you matters to us. Final Compensation Will be determined based on factors such as the selected candidate’s qualifications, relevant experience, skill set, and other job-related considerations. Benefits & PerksInsurance: Medical/dental/vision, 30-day eligibility. Bumble has multiple competitive offerings that will be available to you on the first of the month following date of hire. Unlimited PTO + 1 company-wide week off + Focus Fridays every week Fully paid life and long-term disability insurance 401k with 4% company match if you contribute 6%, 90-day eligibility Monthly wellness benefit and access to Noom, Unmind, and Your Money Line Maternity and Fertility benefit + 26 week paid parental leave Premium App Access Inclusion at Bumble Inc. Bumble Inc. is an equal opportunity employer and we strongly encourage people of all ages, colour, lesbian, gay, bisexual, transgender, queer and non-binary people, veterans, parents, people with disabilities, and neurodivergent people to apply. We're happy to make any reasonable adjustments that will help you feel more confident throughout the process, please don't hesitate to let us know how we can help. In your application, please feel free to note which pronouns you use (For example: she/her, he/him, they/them, etc). AI in Bumble Inc. Hiring At Bumble, we may use AI tools to support parts of our recruitment process — such as helping us record, transcribe, and summarize conversations, and supporting job alignment by comparing resumes and job descriptions to highlight skills and potential roles that may be a good match. These tools help us work more efficiently and stay focused on you during our conversations. Importantly, all hiring decisions are made by people. AI is used only to support our team’s efficiency and improve the candidate experience — not to evaluate or decide on your candidacy. Participation in AI-supported interviews and conversations is completely voluntary and will not impact your candidacy. If you’d prefer to opt out, simply let your recruiter or interviewer know at the start of a call, or anytime during the interview or conversation. Summaries and related data are retained only as long as needed in line with our internal data retention policies. If at any point you’d like a transcription or summary deleted, please contact your recruiter directly. For further information on how we hold and manage your data, please refer to our Privacy Policy. What You'll do Own and drive large-scale, end-to-end ML systems powering recommendations, ranking, and personalization, influencing product and technical direction Design and architect scalable ML platforms and pipelines, integrating data processing, training, evaluation, and deployment (e.g. Spark, Airflow) Build and optimise advanced models using modern ML frameworks (e.g. PyTorch), ensuring performance, scalability, and reliability in production Lead the development of LLM-powered systems and AI agents, including prompt design, fine-tuning, and system integration Establish best practices for experimentation, including robust A/B testing and evaluation methodologies Collaborate cross-functionally at depth, partnering with Product, Engineering, and Data to shape strategy and deliver impactful ML solutions Mentor and elevate engineers across the team, fostering a culture of Respect, ownership, and technical excellence Take ownership of highly ambiguous problem spaces, seeing initiatives through from insight to impact while adapting with an agile mindset About You Typically requires 8–12 years of experience, though we welcome candidates with alternative backgrounds that demonstrate equivalent skills. Deep expertise in machine learning, with significant experience building and scaling production-grade systems Strong proficiency in Python and ML frameworks (e.g. PyTorch, TensorFlow), with experience in recommendation systems, ranking, or NLP Expertise in designing scalable ML and data pipelines using distributed systems (e.g. Spark, Airflow or similar) Experience working with LLMs and building production-ready AI-driven features or systems Demonstrated ability to operate as a senior individual contributor, influencing technical decisions and elevating team capabilities Strong cross-functional collaboration skills, working with purpose and taking ownership of outcomes across teams Advanced AI fluency, with the ability to design, evaluate, and optimise ML systems and guide others in responsible AI practices

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