Senior Machine Learning Engineer

Bumble Inc. • Austin, TX

30d

About The Position

We are seeking a Senior Machine Learning Engineer to build and deploy machine learning models that improve recommendations, ranking, and personalization, driving measurable impact on user experience and engagement. This role involves owning problems end-to-end, from data exploration and feature engineering through to model training, evaluation, and production deployment. You will develop and maintain scalable ML pipelines using tools such as Spark and Airflow to support reliable, high-quality model delivery. Additionally, you will 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, and collaborate cross-functionally with Product and Engineering to translate product questions into ML solutions. You will take ownership of delivering high-quality solutions and see work through from insight to impact, balancing speed and rigor, and apply responsible AI practices, ensuring fairness, transparency, and safety are considered in model development and deployment.

Requirements

• 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

Responsibilities

• 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

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed