Cloud-Based Machine Learning Operations Expert
5 days ago
Daily Pay is a pioneering worktech company that's revolutionizing the way people get paid. As the industry's leading earned wage access solution, we use an award-winning technology platform to empower top employers to build stronger relationships with their employees. Our voluntary employee benefit enables workers everywhere to feel more motivated to work harder and stay longer on the job while supporting their financial well-being outside of the workplace. With operations throughout the United States and in Belfast, Daily Pay is headquartered in New York City. For more information, visit our Press Center.
The Role: We're seeking a highly skilled Senior MLOps Engineer to join our growing team in Belfast. This individual will play a crucial role in maturing and scaling our machine learning infrastructure and processes, ensuring the reliability, scalability, and performance of our ML models in production.
This role requires a strong background in MLOps principles, cloud technologies (AWS), and a passion for building robust and efficient systems. The successful candidate will collaborate closely with data scientists, engineers, and product teams to deliver high-quality ML solutions that directly impact our business.
Mission Statement: Our Data Science Team's mission is critical for the continuous development and success of our product, understanding the needs of our customers and partners, and maintaining Daily Pay's leading role in the early wage access industry.
We're looking for a staff MLOps Engineer who will be instrumental in helping to realize this vision by enabling efficient and effective deployment and management of machine learning models.
Key Responsibilities:
- Design and implement scalable and efficient ML pipelines and workflows, encompassing model training, deployment, monitoring, and retraining.
- Collaborate with data scientists, engineers, and product teams to deliver high-quality ML solutions that directly impact our business.
- Manage and optimize our AWS cloud infrastructure for machine learning, ensuring cost-effectiveness, security, and high availability.
- Develop and maintain robust CI/CD pipelines for continuous integration and deployment of ML models and related infrastructure.
- Build and maintain comprehensive monitoring and alerting systems for our ML infrastructure and models, leveraging tools like Data Dog to ensure system health and performance.
- Provide guidance and support to junior team members.
- Continuously optimize ML model performance, data pipelines, and infrastructure to meet evolving business needs.
- Ensure the security and compliance of our machine learning applications and data pipelines, adhering to industry best practices and regulations.
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