Senior Software Developer working on ML Infrastructure and Deployment at Verafin. Helping develop cutting - edge fraud detection tools alongside analytics teams using AWS and Terraform.
About the role
- Senior Machine Learning Engineer focused on scalability and productionisation at Bumble, building advanced ML models for actionable insights and recommendations. Collaborate with teams to ensure continuous performance and reliability of ML systems.
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
- 5+ 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.
- Unlimited Paid Time Off: Take the time you need.
- Company-wide Week Off: Annual collective rest for the entire company.
- Focus Fridays: No meetings, emails, or deadlines—just deep work.
Job title
Job type
Experience level
Salary
Degree requirement
Tech skills
Location requirements
Machine Learning Engineer developing advanced SLAM systems for autonomous trucking environments at Bot Auto. Collaborating with cross - functional teams to optimize mapping solutions and ensure operational stability.
Graduate Deep Learning Algorithm Developer developing perception technologies for autonomous driving. Tackling challenges in object detection and 3D perception using state - of - the - art deep learning models.
Principal AI/ML Engineer leading the AI/ML infrastructure development for WEX's risk service needs. Focused on innovative engineering and technology solutions within a high - stakes environment.
AI/ML Engineer developing solutions in artificial intelligence for HPE. Responsible for conducting research, designing AI solutions, and mentoring team members.
Machine Learning Engineer focusing on modeling cancer cells and developing related tools. Collaborating with researchers and scientists to advance cancer treatment through ML.
Machine Learning Engineer II developing production - grade ML models for fraud detection at GEICO. Collaborating on system architecture and ensuring optimal performance of fraud assessment systems.
AI/ML Engineer III designing and architecting AI solutions at Hewlett Packard Enterprise. Collaborating with teams to drive innovation and tackle complex problems.
AI/ML Engineer deploying state - of - the - art AI models to solve real - world problems at Brain Co. Working in healthcare, government, and energy sectors for impactful results.
Trainer at WeAndTheMany facilitating learning by sharing experiences and creating interactive sessions. Engaging with students to enhance their skills and knowledge through dynamic teaching methods.