Machine Learning Engineer at DentalMonitoring developing and improving ML models for orthodontic treatment solutions. Engage in deep learning and computer vision tasks within a hybrid work environment.
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.
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