5-8 years of experience in machine learning roles, open to non-traditional backgrounds that show relevant skills
Strong background in deploying machine learning models in live environments
Proficiency in Python; expertise in frameworks like PyTorch or TensorFlow
Experience with data pipeline management and distributed systems (e.g., Spark, Airflow)
Knowledge of experimentation methodologies, including A/B testing
Strong interpersonal skills for effective cross-functional collaboration
Agile mindset with a focus on adapting to data-driven insights and priorities
Awareness of responsible AI practices and able to implement them in projects
Responsibilities
Build and deploy machine learning models to enhance user experiences and engagement
Manage end-to-end problem-solving, from data exploration to model deployment
Develop scalable ML pipelines using technologies like Spark and Airflow
Utilize modern ML frameworks to design, train, and optimize models
Contribute to experimentation frameworks for iterating model performance
Collaborate with Product and Engineering to transform product questions into ML solutions
Ensure high-quality outcomes through ownership and accountability for project deliverables
Apply responsible AI practices to ensure fairness and transparency in model development
Benefits
Access to advanced tools and technologies in machine learning
Collaborative work environment that values innovation and agility
Support for professional development and continuous learning
Opportunities to work on impactful projects that enhance user engagement
Focus on responsible AI practices, promoting ethical considerations in the technology
Full Job Description
What you'll do
Build and deploy machine learning models that improve recommendations, ranking, and personalization, driving measurable impact on user experience and engagement
Own problems end-to-end, from data exploration and feature engineering through to model training, evaluation, and production deployment
Develop and maintain scalable ML pipelines using tools such as Spark and Airflow to support reliable, high-quality model delivery
Apply modern ML frameworks (e.g. PyTorch or TensorFlow) to design, train, and optimize models in production environments
Contribute to experimentation frameworks, including A/B testing and offline evaluation, to iterate on model performance with an agile mindset
Collaborate cross-functionally with Product and Engineering, working with purpose to translate product questions into ML solutions
Take ownership of delivering high-quality solutions and see work through from insight to impact, balancing speed and rigor
Apply responsible AI practices, ensuring fairness, transparency, and safety are considered in model development and deployment
About You
Typically requires 5-8 years of experience, though we welcome candidates with alternative backgrounds that demonstrate equivalent skills.
Strong experience building and deploying machine learning models in production environments
Proficiency in Python and experience with at least one major ML framework (e.g. PyTorch, TensorFlow)
Experience working with data pipelines and distributed systems (e.g. Spark, Airflow) to support ML workflows
Familiarity with experimentation methodologies such as A/B testing and model evaluation techniques
Ability to collaborate effectively across functions, demonstrating strong ownership and a collaborative mindset
Demonstrates an agile mindset, adapting approaches based on data and evolving priorities while maintaining focus on outcomes
Growing AI fluency, with the ability to independently apply ML techniques and emerging tools (including LLMs) to solve problems responsibly
Final Compensation
Will be determined based on factors such as the selected candidate's qualifications, relevant experience, skill set, and other job-related considerations.
About Bumble
Bumble is an online dating app that allows users to connect with potential partners. The company was founded in 2014 and is headquartered in Austin, Texas. Bumble offers a range of features, including photo verification, video chat, and voice calls. The company serves a variety of demographics, including young adults and the LGBTQ+ community.
