Recommendation Systems Engineer Jobs

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1d ago

Principal Machine Learning Engineer, Matching and Recommendations

Bumble Inc. New York, NY

New York, NY

1d ago

$345k - $410k/yr Full time Ai Ml Artificial Intelligence Big Data

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Job Description

Bumble is hiring a Principal Machine Learning Engineer to define and lead machine learning strategy for next-generation recommendation systems. This role is hands-on across retrieval, ranking, personalization, experimentation, and marketplace optimization, with responsibility for measurable improvements in engagement and safety.

Key Responsibilities

Define and lead technical strategy for AI and machine learning systems powering recommendations, ranking, and personalization across Bumble products, with 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), including sub-agents, tools, and MCP integrations
Architect end-to-end machine learning pipelines that connect data processing (for example, Spark and 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 needs into impactful ML solutions, influencing at senior levels
Mentor and elevate senior individual contributors, fostering a culture of Excellence, Curiosity, and continuous learning within the ML community
Own complex and ambiguous problem spaces, taking initiatives from insight to impact while applying an agile mindset
Champion responsible AI practices by embedding fairness, transparency, and user safety into machine learning systems

Required Qualifications

Typically requires 10 to 15 years of experience; alternative backgrounds demonstrating equivalent skills are welcome
Deep expertise in machine learning with hands-on experience building and deploying large-scale production systems
Strong proficiency in Python and at least one major ML framework (for example, PyTorch or TensorFlow), including experience with recommendation systems, ranking models, or NLP
Expertise in prompting and fine-tuning LLMs, with experience building production AI Agents
Proven experience designing scalable data and ML pipelines using tools such as Spark, Airflow, or similar distributed systems
Ability to operate as a senior individual contributor, influencing technical strategy and decisions without direct authority
Effective cross-functional partnership with purpose, taking ownership of outcomes in complex organizational environments
Track record of mentoring and uplifting others, role modeling Respect and Excellence, and building inclusive, high-performing teams
Strong AI fluency, including the ability to independently design, evaluate, and optimize ML systems and guide others in responsible and effective AI use

Technologies

Python
PyTorch
TensorFlow
Large Language Models (LLMs)
MCP
Spark
Airflow
A/B testing

Location and Work Setup

New York, NY (onsite)

Compensation

USD 345,000 - 410,000 per year

Final compensation will be determined based on qualifications, relevant experience, skill set, and other job-related considerations.

Inclusion at Bumble Inc.

Bumble Inc. is an equal opportunity employer and strongly encourages people of all ages, color, lesbian, gay, bisexual, transgender, queer and non-binary people, veterans, parents, people with disabilities, and neurodivergent people to apply
Reasonable adjustments are available throughout the process; applicants are encouraged to let the team know how support would help
In the application, candidates may note their pronouns (for example, she/her, he/him, they/them)

AI Use in the Hiring Process

Bumble may use AI tools to support parts of recruitment, such as recording, transcribing, summarizing conversations, and comparing resumes and job descriptions to highlight skills and potential role matches
Hiring decisions are made by people; AI supports team efficiency and the candidate experience rather than evaluating or deciding candidacy
Participation in AI-supported interviews and conversations is voluntary and will not impact candidacy
Candidates who prefer to opt out can notify their recruiter or interviewer at the start of a call or at any point during the conversation
Summaries and related data are retained only as long as needed under internal data retention policies
Candidates can request transcription or summary deletion by contacting their recruiter

Fraudulent Candidate Detection

The applicant tracking system analyzes signals relating to device, IP, email, and phone data to protect applicants and the hiring process from fraudulent applications
Signals are used for internal review only and do not provide a definitive determination of identity or intent
No applicant is rejected, advanced, or otherwise affected based solely on this analysis without human review

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