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Bumble is looking for a talented Engineering Manager - Machine Learning to join the Trust ML team and help drive our mission to create a world where all relationships are healthy and equitable. We're looking for an ML leader with strong technical understanding, business acumen and proven track record of leading small high-performing teams of data scientists and machine learning engineers. At Bumble, the Engineering Manager role is all about leadership, execution, and delivery - while also contributing to the broader community and shaping our engineering culture!
Trust and Safety is truly at the heart of Bumble Inc.'s mission to create a world where all relationships are healthy and equitable through kind connections. We believe that everyone deserves a safe and comfortable place to make empowered, respectful, and meaningful connections. Our technology-related work in the Trust space is a key part of this. We're responsible for complex and meaningful problems including member and content authenticity; detecting and combating toxic behaviour and content whilst encouraging kindness; creating and maintaining support, moderation, and operational tooling; and using a range of technologies leveraging machine learning at their core.
What you'll do:
- Take the lead in collaboratively designing, delivering and maintaining our machine learning services, in close collaboration with Trust Product Management;
- Collaborate with Machine Learning Engineers and the MLOps Core Team to ensure our architectural choices and tech stack align with the broader tech and product strategy;
- Drive continuous improvement in processes and technology, ensuring the team meets quality standards and delivery commitments while maintaining an inclusive, high-performance culture;
- Create tangible objectives that link team deliverables with overall Group vision in close partnership with Trust Area leadership. Monitor progress and provide visibility to all stakeholders;
- Actively spot dependencies, inefficiencies, or roadblocks, pushing for both short- and long-term resolutions;
- Oversee career development for direct reports, setting clear expectations, providing feedback, and ensuring team members have a clear path for progression;
- Support the wider Bumble's technology team in adopting modern practices and leveraging machine learning to enhance our members' experience across their entire journey with our products;
- Be an ambassador of Bumble Inc. culture and values, who sets the standards by example!
About you and your experience:
- 1-2 years of people management experience in an engineering-driven environment heavily focused on data science and machine learning;
- Proven track record of leading successful end-to-end machine learning projects (NLP, Computer Vision, pattern detection), either directly as a contributor or as a people manager;
- Experience in working cross-functionally in partnership with product and data science;
- Comfortable working in agile or hybrid delivery environments, with a collaborative and adaptable mindset;
- Direct exposure to modern MLOps infrastructures, from training to internet scale GPU inference in multiple regions;
- Ready to champion and educate others in using machine learning to solve business challenges or customer pain points;
- Able to balance strategic and tactical demands, challenging the status quo and empowering your team to innovate;
- Strong interpersonal and communication skills: You build trust with stakeholders, champion a positive team environment, and ensure clarity in goals and execution.
Inclusion at Bumble Inc.
Bumble Inc. is an equal opportunity employer and we strongly encourage people of 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).