Hybrid Machine Learning Engineer

at Bumble Inc.

• Job title: Machine Learning Engineer
• Job type: Full Time
• Experience level: Junior, Mid level
• Salary: $145,000 - $175,000 per year
• Degree requirement: Postgraduate Degree
• Tech skills: Airflow, AWS, Cloud, Docker, Google Cloud Platform, Kubernetes, Python, PyTorch, Ray, Tensorflow
• Location requirements: Hybrid, Austin, United States

About the role

• Senior Machine Learning Engineer at Bumble creating and optimizing ML models. Collaborating across technical teams to enhance user experiences through data-driven insights.

Responsibilities

• Design, build and optimise ML pipelines and production systems that train, evaluate and serve recommendation models efficiently and at scale.
• Work in a cross-functional team alongside data scientists, machine learning scientists, software engineers and both technical and non-technical stakeholders.
• Partner with ML Scientists to translate research models into efficient, maintainable, and well-tested production systems.
• Implement monitoring, observability, and retraining strategies to ensure continuous model performance in a dynamic, global environment.
• Contribute to the evolution of our ML infrastructure, including CI/CD, model registries, and feature stores.
• Diagnose and resolve production ML issues, such as data inconsistencies and model drift, to identify and resolve infrastructure bottlenecks.
• Champion engineering best practices for scalability, reliability, and reproducibility across the ML lifecycle.

Requirements

• 2+ years of relevant industry experience.
• An advanced degree in Computer Science, Mathematics or a similar quantitative discipline.
• Strong software engineering background. You write clean, scalable, and maintainable code in Python or similar languages.
• Proven experience deploying and operating ML systems in production environments.
• Deep understanding of MLOps and infrastructure concepts: CI/CD for ML, feature stores, model serving, observability, and versioning.
• Experience with modern ML frameworks (e.g. PyTorch, TensorFlow) and orchestration tools (e.g. Airflow, Kubeflow, SageMaker, Ray).
• Familiarity with containerisation and cloud-native environments (e.g. Docker, Kubernetes, GCP/AWS).
• Skilled at debugging complex, distributed ML systems and optimising for performance at scale.
• Excellent communicator and collaborator. You communicate effectively with scientists, engineers, and non-technical stakeholders.
• Interested in contributing to the responsible development of ML and AI, with a focus on building systems that are fair, equitable and accountable.

Benefits

• Medical
• Dental
• Vision
• 401(k) match
• Unlimited Paid Time Off Policy
• Maven Fertility: $10,000 lifetime benefit for fertility, adoption, abortion care, and more.
• 26 Weeks Parental Leave: For both primary and secondary caregivers.
• Family & Compassionate Leave: Inclusive of domestic violence recovery.
• Company-wide Week Off: Annual collective rest for the entire company.
• Focus Fridays: No meetings, emails, or deadlines—just deep work.