
Principal Machine Learning Engineer, Matching & Recommendations
About this role
Based in Austin, TX or Remote US, the Principal Machine Learning Engineer, Matching & Recommendations role at Bumble Inc. involves setting the technical direction for matching and recommendation systems. This position is well-suited for a senior technical professional with extensive experience building production-grade machine learning solutions and mentoring teams.
Role Overview
Bumble Inc. is hiring a Principal Machine Learning Engineer for its Matching & Recommendations team in Austin, TX. The person in this role will define the technical and machine learning strategy for recommendation, ranking, and personalization systems while remaining hands-on. The position involves collaborating across Engineering, Product, Data Science, and Analytics to address complex marketplace challenges and improve member outcomes.
Key Responsibilities
Requirements
Skills and Tools
Salary and Benefits
About the Company
Bumble Inc. is the parent company of Bumble Date, BFF, and Badoo. Founded by Whitney Wolfe Herd in 2014, the platform was initially built with women at the center to facilitate healthy and equitable relationships and connections across dating and friendship.
How to Apply
Interested candidates should apply directly on the official Bumble careers page.
Skills and tech stack
Questions candidates ask
What is the salary range for this position?
The final compensation is between $345,000 and $410,000, determined by qualifications, relevant experience, and skill set.
Where is the job located?
The role is located in Austin, TX.
How many years of experience are required?
The position typically requires 10 to 15 years of experience, though candidates with alternative backgrounds demonstrating equivalent skills are also welcomed.
What core frameworks and tools are expected?
Candidates should have strong proficiency in Python, major machine learning frameworks like PyTorch or TensorFlow, and experience with distributed systems such as Spark and Airflow.