Machine Learning Engineer (UK)

Bumble Inc.; Greater London; On-site; GBP 70,000 - 120,000; Full time

Job summary

Bumble Inc. is looking for a hands-on ML Engineer to build and deploy models that power personalized recommendations across Bumble products in London.

You will own end-to-end ML projects from data exploration and feature engineering to training, evaluation, and production deployment.

Qualifications

• 3 years hands-on experience building and shipping ML models in production.
• Strong Python and ML framework proficiency (PyTorch or TensorFlow).
• Experience in recommender systems, ranking or personalization preferred.
• Knowledge of MLOps, CI/CD for ML, feature stores, model serving, observability, versioning.
• Familiarity with Docker/Kubernetes and cloud-native environments.
• Experience with experimentation methodologies (A/B testing).
• Ability to adapt approaches based on data and priorities.

Responsibilities

• Explore, develop, and deliver cutting-edge technology using deep learning and ML to personalize recommendations at Bumble
• Own defined problems end-to-end, from data exploration and feature engineering through to model training, evaluation, and production deployment
• Apply modern ML frameworks to design, train, and optimise models in production environments
• Contribute to experimentation frameworks, including A/B testing and offline evaluation, to iterate on model performance with an agile mindset
• Maintain and monitor production models, diagnose issues, and iterate to keep them reliable at scale
• Take ownership of delivering high-quality solutions and see work through from insight to impact, balancing speed and rigor
• Apply responsible AI practices, ensuring fairness, transparency, and safety are considered in model development and deployment

Skills

Python

ML frameworks (PyTorch/TensorFlow)

MLOps

Docker/Kubernetes

Cloud platforms

Experimentation (A/B)

Agile

LLMs

Tools

Docker

Kubernetes

GCP

AWS

MLflow

Job description

WHAT YOU WILL BE DOING

• Explore, develop, and deliver cutting-edge technology using the latest advances in deep learning and machine learning to personalize recommendations at Bumble
• Own defined problems end-to-end, from data exploration and feature engineering through to model training, evaluation, and production deployment
• Apply modern ML frameworks (e.g., PyTorch or TensorFlow) to design, train, and optimise models in production environments
• Contribute to experimentation frameworks, including A/B testing and offline evaluation, to iterate on model performance with an agile mindset
• Maintain and monitor production models, diagnose issues, and iterate to keep them reliable at scale.
• Take ownership of delivering high-quality solutions and see work through from insight to impact, balancing speed and rigor
• Apply responsible AI practices, ensuring fairness, transparency, and safety are considered in model development and deployment

WE’D LOVE TO MEET SOMEONE WITH

• Around 3 years of hands‑on experience building and shipping machine learning models in production.
• Strong programming skills in Python and solid proficiency with an ML framework such as PyTorch or TensorFlow.
• Industry experience in researching or applying machine learning, especially if in recommender systems, ranking or personalisation
• Good understanding of MLOps and infrastructure concepts: CI/CD for ML, feature stores, model serving, observability, and versioning.
• Familiarity with containerisation and cloud‑native environments (e.g. Docker, Kubernetes, GCP).
• Familiarity with experimentation methodologies such as A/B testing and model evaluation techniques
• Demonstrates an agile mindset, adapting approaches based on data and evolving priorities while maintaining focus on outcomes
• Growing AI fluency, with the ability to independently apply ML techniques and emerging tools (including LLMs) to solve problems responsible

AN ADDED BONUS IF YOU HAVE

• practical experience with recommendation systems, ranking, search or personalisation
• expertise in modern machine learning architectures (e.g., transformers, graph neural networks, contrastive learning, and multi‑modal embeddings)

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.

Inclusion at Bumble Inc.

Bumble Inc. is an equal opportunity employer and we strongly encourage people of all ages, color, 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 might 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.

Fraudulent Candidate Detection

Our applicant tracking system analyzes signals relating to device, IP, email, and phone data associated with each application to protect applicants and our hiring process from fraudulent applications. These signals provide indicators for internal review only and do not constitute a definitive determination of identity or intent. No applicant is rejected, advanced, or otherwise affected based solely on this analysis without human review

For further information on how we hold and manage your data, please refer to our Privacy Policy.