Principal Machine Learning Engineer, Matching and Recommendations

About the role

Define and lead the technical strategy for AI and Machine Learning systems that power recommendations, ranking, and personalization across Bumble products, delivering measurable improvements in user engagement and safety.

Design, develop, and deploy production-grade models using modern ML frameworks such as PyTorch, ensuring scalability and reliability in high-traffic environments.

Build and deploy production AI Agents using raw and fine-tuned foundational Large Language Models (LLMs), along with sub-agents, tools, and MCP integrations.

Architect end-to-end ML pipelines, integrating data processing (e.g. Spark, Airflow) with model training, evaluation, and deployment workflows.

Drive experimentation frameworks, including A/B testing and offline evaluation, to continuously improve model performance and product outcomes.

Partner cross-functionally with Product, Engineering, and Data leadership to translate business challenges into impactful ML solutions, collaborating with purpose and influencing at senior levels.

Mentor and elevate senior individual contributors, fostering a culture of Excellence, Curiosity, and continuous learning across the ML community.

Champion responsible AI practices, ensuring fairness, transparency, and user safety are embedded into all machine learning systems.

Responsibilities

• Define and lead the technical strategy for AI and Machine Learning systems that power recommendations, ranking, and personalization across Bumble products, delivering measurable improvements in user engagement and safety.
• Design, develop, and deploy production-grade models using modern ML frameworks such as PyTorch, ensuring scalability and reliability in high-traffic environments.
• Build and deploy production AI Agents using raw and fine-tuned foundational Large Language Models (LLMs), along with sub-agents, tools, and MCP integrations.
• Architect end-to-end ML pipelines, integrating data processing (e.g. Spark, Airflow) with model training, evaluation, and deployment workflows.
• Drive experimentation frameworks, including A/B testing and offline evaluation, to continuously improve model performance and product outcomes.
• Partner cross-functionally with Product, Engineering, and Data leadership to translate business challenges into impactful ML solutions, collaborating with purpose and influencing at senior levels.
• Mentor and elevate senior individual contributors, fostering a culture of Excellence, Curiosity, and continuous learning across the ML community.
• Champion responsible AI practices, ensuring fairness, transparency, and user safety are embedded into all machine learning systems.

Requirements

Typically requires 10-15 years of experience, though we welcome candidates with alternative backgrounds that demonstrate equivalent skills.

Deep expertise in machine learning, with hands-on experience building and deploying large-scale systems in production environments.

Strong proficiency in Python and at least one major ML framework (e.g. PyTorch, TensorFlow), with experience in areas such as recommendation systems, ranking models, or NLP.

Expertise in prompting and fine-tuning Large Language Models (LLMs) and building production AI Agents.

Proven experience designing scalable data and ML pipelines using tools such as Spark, Airflow, or similar distributed systems.

Demonstrated ability to operate as a senior individual contributor, influencing technical strategy and decision-making without direct authority.

Experience partnering effectively across functions, collaborating with purpose and taking ownership of outcomes in complex organizational environments.

A track record of mentoring and uplifting others, role-modeling Respect and Excellence while building inclusive, high-performing teams.

Strong AI fluency, with the ability to independently design, evaluate, and optimise ML systems, and guide others in the responsible and effective application of AI.

Qualifications

Deep expertise in machine learning, with hands-on experience building and deploying large-scale systems in production environments.

Strong proficiency in Python and at least one major ML framework (e.g. PyTorch, TensorFlow), with experience in areas such as recommendation systems, ranking models, or NLP.

Expertise in prompting and fine-tuning Large Language Models (LLMs) and building production AI Agents.

Proven experience designing scalable data and ML pipelines using tools such as Spark, Airflow, or similar distributed systems.

Demonstrated ability to operate as a senior individual contributor, influencing technical strategy and decision-making without direct authority.

Experience partnering effectively across functions, collaborating with purpose and taking ownership of outcomes in complex organizational environments.

A track record of mentoring and uplifting others, role-modeling Respect and Excellence while building inclusive, high-performing teams.

Strong AI fluency, with the ability to independently design, evaluate, and optimise ML systems, and guide others in the responsible and effective application of AI.

Skills

Deep expertise in machine learning, with hands-on experience building and deploying large-scale systems in production environments.

Strong proficiency in Python and at least one major ML framework (e.g. PyTorch, TensorFlow), with experience in areas such as recommendation systems, ranking models, or NLP.

Expertise in prompting and fine-tuning Large Language Models (LLMs) and building production AI Agents.

Proven experience designing scalable data and ML pipelines using tools such as Spark, Airflow, or similar distributed systems.

Demonstrated ability to operate as a senior individual contributor, influencing technical strategy and decision-making without direct authority.

Experience partnering effectively across functions, collaborating with purpose and taking ownership of outcomes in complex organizational environments.

A track record of mentoring and uplifting others, role-modeling Respect and Excellence while building inclusive, high-performing teams.

Strong AI fluency, with the ability to independently design, evaluate, and optimise ML systems, and guide others in the responsible and effective application of AI.

Benefits

Insurance: 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 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.

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.

Sources: Bumble Inc. Recruitment Process.