Senior Machine Learning Engineer
14 Oct 2025
Austin, TX, USA
Verified by Turrior
Content + Source + Freshness • 13 Dec 2025 • 95% confidence
85 / 100
Offer value
This role offers a high value due to its advanced technical requirements, significant impact on product functionality, and growth opportunities within a progressive company.
- Key role affecting millions of Bumble users
- Strong cross-functional collaboration
- Potential for personal and professional growth
- Requires significant experience and coding fluency
Pros
- Direct influence on critical features used by millions of users
- Collaborative environment with diverse teams and skill sets
- Commitment to personal development and mentorship
Cons
- High competition due to significant qualifications required
- Requires regular on-site presence in Austin
- Limited visa sponsorship options for international applicants
Who it's for
Senior / Lead • Hybrid / onsite Mondays to Wednesdays
Good fit
- Senior machine learning engineers
- Technologists focused on user-driven impact
- Those looking to enhance their skills in a leader role
Not recommended for
- Novices in machine learning or software development
- Preference for completely remote work...
- Individuals lacking coding experience in relevant languages
Motivation fit
Desire to work on large-scale ML projectsInterest in collaborative problem-solvingCommitment to responsible AI development practices
Key skills
Machine learning techniquesMLOps and infrastructure managementPython programmingCollaboration across technical and non-technical teams
Score: 85/100 AI verified analysis
About the job
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).
As a Senior Machine Learning Engineer focused on scalability and productionisation, you will bring advanced machine learning models to life in production, from content understanding systems that interpret profiles, photos and text, to recommendation models that shape every match. You will build and scale the pipelines, infrastructure and automation that transform experimentation into reliable, high-impact features for our members.
What you'll do
- Design, build and optimise ML pipelines and production systems that train, evaluate and serve recommendation models efficiently and at scale.
- Work in a cross-functional team alongside data scientists, machine learning scientists, software engineers and both technical and non-technical stakeholders.
- Partner with ML Scientists to translate research models into efficient, maintainable, and well-tested production systems.
- Implement monitoring, observability, and retraining strategies to ensure continuous model performance in a dynamic, global environment.
- Contribute to the evolution of our ML infrastructure, including CI/CD, model registries, and feature stores.
- Diagnose and resolve production ML issues, such as data inconsistencies and model drift, to identify and resolve infrastructure bottlenecks.
- Champion engineering best practices for scalability, reliability, and reproducibility across the ML lifecycle.
Minimum requirements
- 5+ years of relevant industry experience.
- An advanced degree in Computer Science, Mathematics or a similar quantitative discipline.
- Strong software engineering background. You write clean, scalable, and maintainable code in Python or similar languages.
- Proven experience deploying and operating ML systems in production environments.
- Deep understanding of MLOps and infrastructure concepts: CI/CD for ML, feature stores, model serving, observability, and versioning.
- Experience with modern ML frameworks (e.g. PyTorch, TensorFlow) and orchestration tools (e.g. Airflow, Kubeflow, SageMaker, Ray).
- Familiarity with containerisation and cloud-native environments (e.g. Docker, Kubernetes, GCP/AWS).
- Skilled at debugging complex, distributed ML systems and optimising for performance at scale.
- Excellent communicator and collaborator. You communicate effectively with scientists, engineers, and non-technical stakeholders.
- Interested in contributing to the responsible development of ML and AI, with a focus on building systems that are fair, equitable and accountable.
Why join us
- Own meaningful projects that directly impact millions of Bumble users.
- Learn and grow in a high-performing engineering team committed to mentorship and learning.
- Be part of a culture that values respect, excellence, curiosity, courage and joy.
- Enjoy competitive compensation, equity, and world-class benefits.
Location
- This role is based in Austin, and we ask that you’re within a commutable distance to this office, so that you’re able to come onsite regularly to collaborate across engineering teams.
- We have a hybrid environment that requires you to be in the office Monday - Wednesday.
- Please note: We are unable to offer Visa sponsorship at this time
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 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.
