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HomeCompaniesBumbleincPrincipal Machine Learning Engineer, Matching and Recommendations

Principal Machine Learning Engineer, Matching and Recommendations

Bumbleinc · US TX Austin · Hybrid · Active · $345,000–$410,000 / year · Lever

Job facts

FieldValue
CompanyBumbleinc
TitlePrincipal Machine Learning Engineer, Matching and Recommendations
Normalized title-
Department / teamData & Analytics / Machine Learning
LocationUnited States
Work modelHybrid / Hybrid
Employment typeEmployee Regular/Permanent
Salary$345,000–$410,000 / year
Statusactive
ATS providerLever
Posted / first seen2026-04-01 / 2026-05-29
Changed / last seen2026-06-02 / 2026-06-06

Related slices

PageWhat it containsOpen
Company jobsActive postings from Bumbleinc.Open
Company breakdownsRole, location, ATS, and work model facets for this company.Open
ATS provider jobsActive postings observed through Lever.Open
Provider filtered searchThe same provider as a filtered job collection.Open
Department jobsActive postings in Data & Analytics.Open
Work model jobsActive Hybrid postings.Open
Lifecycle eventsOpen, update, close, and reopen events for this posting.Open
Original postingCanonical source or apply URL captured from the ATS.Open

Linked records

CompanyBumbleinc
Sourceda9ee548-3f84-4651-bf1a-d328dba89816
ATS providerLever

Description

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 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 Take ownership of complex, ambiguous problem spaces, seeing initiatives through from insight to impact while adapting approaches with an agile mindset Champion responsible AI practices, ensuring fairness, transparency, and user safety are embedded into all machine learning systems About You 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 organisational environments A track record of mentoring and uplifting others, role modelling 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

Full job record

Job ID4a6a8212ceae8a7288e5606a114de7be5512a7f8
Org ID0b6acf11-9e2a-4f79-b828-20a02fc8b8aa
Source IDda9ee548-3f84-4651-bf1a-d328dba89816
Board IDda9ee548-3f84-4651-bf1a-d328dba89816
Providerlever
Provider Job Keya9f321fc-b38d-450a-a3ba-3174e37ba0f3
TitlePrincipal Machine Learning Engineer, Matching and Recommendations
Normalized Title
Statusactive
Activeyes
Location TextUS TX Austin
DepartmentData & Analytics
TeamMachine Learning
Employment TypeEmployee - Regular/Permanent
Workplace Typehybrid
Remote Policyhybrid
CountryUnited States
Region
City
Salary RawUSD 345000-410000 per-year-salary
Salary Min345,000
Salary Max410,000
Salary CurrencyUSD
Salary Periodyear
Source URLhttps://jobs.lever.co/bumbleinc/a9f321fc-b38d-450a-a3ba-3174e37ba0f3
Apply URLhttps://jobs.lever.co/bumbleinc/a9f321fc-b38d-450a-a3ba-3174e37ba0f3/apply
First Seen At2026-05-29 07:02:25Z
Last Seen At2026-06-06 07:57:37Z
Last Checked At2026-06-06 07:57:37Z
Last Changed At2026-06-02 10:48:56Z
Inactive At
Source Posted At2026-04-01 20:25:51Z
Source Updated At
Raw Payload Uris3://job-postings-prod-raw-590183727216/raw/provider=lever/board=bumbleinc/date=2026-06-06/2026-06-06T07-57-36-267Z-4ce06b427af14da06f691adac7aaf815018bed5d5394ceb978364abffac9854a.json
Event Fields
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  "last_changed_at": "2026-06-02T10:48:56.048Z",
  "active_status": "active"
}
Parsed Structured
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  "remote_policy": "hybrid",
  "salary_period": "year",
  "workplace_type": "hybrid",
  "salary_currency": "USD"
}
Extensions
{}
Native Structured
{
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      "text": "What you'll do",
      "content": "<div>\n\n<li>\n<p>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</p>\n</li>\n<li>\n<p>Design, develop, and deploy production-grade models using modern ML frameworks such as PyTorch , ensuring scalability and reliability in high-traffic environments&nbsp;</p>\n</li>\n<li>\n<p>Build and deploy production AI Agents using raw and fine-tuned foundational Large Language Models (LLMs), along with sub-agents, tools, and MCP integrations</p>\n</li>\n<li>\n<p>Architect end-to-end ML pipelines, integrating data processing (e.g. Spark, Airflow) with model training, evaluation, and deployment workflows&nbsp;</p>\n</li>\n<li>\n<p>Drive experimentation frameworks, including A/B testing and offline evaluation, to continuously improve model performance and product outcomes</p>\n</li>\n<li>\n<p>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</p>\n</li>\n<li>\n<p>Mentor and elevate senior individual contributors, fostering a culture of Excellence, Curiosity, and continuous learning across the ML community</p>\n</li>\n<li>\n<p>Take ownership of complex, ambiguous problem spaces, seeing initiatives through from insight to impact while adapting approaches with an agile mindset</p>\n</li>\n<li>\n<p>Champion responsible AI practices, ensuring fairness, transparency, and user safety are embedded into all machine learning systems</p>\n</li>\n\n</div>"
    },
    {
      "text": "About You",
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    }
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  "country": "US",
  "createdAt": 1775075151228,
  "updatedAt": null,
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