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About Us
DailyPay is transforming the way people get paid. As a worktech company and the industry’s leading on demand pay solution, DailyPay uses an award-winning technology platform to help America’s top employers build stronger relationships with their employees. This 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.
About Us
DailyPay is transforming the way people get paid. As a worktech company and the industry’s leading on demand pay solution, DailyPay uses an award-winning technology platform to help America’s top employers build stronger relationships with their employees. This 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.
DailyPay is headquartered in New York City, with operations throughout the United States as well as in Belfast. For more information, visit DailyPay's Press Center.
The Role
We are seeking a highly skilled and motivated Senior MLOps Engineer to join our growing team in Belfast. You 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. You will collaborate closely with data scientists, engineers, and product teams to deliver high-quality ML solutions that directly impact our business.
The mission of the Data Science Team is critical for the continuous development and success of our product, understanding the needs of our customers and partners, and maintaining DailyPay’s leading role in the early wage access industry. As a staff MLOps Engineer, you will be instrumental in helping to realize this vision for DailyPay by enabling efficient and effective deployment and management of machine learning models.
How You Will Make An Impact
- Design and Implement MLOps Solutions: Design and implement scalable and efficient ML pipelines and workflows, encompassing model training, deployment, monitoring, and retraining. Contribute to the development and implementation of MLOps best practices
- Cloud Infrastructure Management: Manage and optimize our AWS cloud infrastructure for machine learning, ensuring cost-effectiveness, security, and high availability
- CI/CD Pipeline Development: Develop and maintain robust CI/CD pipelines for continuous integration and deployment of ML models and related infrastructure
- Monitoring and Observability: Build and maintain comprehensive monitoring and alerting systems for our ML infrastructure and models, leveraging tools like DataDog to ensure system health and performance
- Collaboration and Mentorship: Collaborate effectively with data scientists, engineers, and other stakeholders. Provide guidance and support to junior team members
- Performance Optimization: Continuously optimize ML model performance, data pipelines, and infrastructure to meet evolving business needs
- Security and Compliance: Ensure the security and compliance of our machine learning applications and data pipelines, adhering to industry best practices and regulations
- Problem Solving and Troubleshooting: Proactively identify and resolve issues related to ML model performance, data integrity, and infrastructure
What You Bring To The Team
- Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field
- 3+ years of experience in machine learning operations, data engineering, or related roles
- AWS Proficiency: Strong understanding of AWS services (e.g., EC2, S3, Lambda, SageMaker, ECS) and cloud infrastructure management
- Programming and ML Frameworks: Proficiency in Python and experience with ML frameworks such as scikit-learn, TensorFlow, or PyTorch
- CI/CD Experience: Experience with CI/CD tools and practices (e.g., GitHub Actions, Jenkins) and the ability to design and implement efficient CI/CD pipelines
- Containerization and Orchestration: Knowledge of containerization and orchestration technologies (e.g., Docker, Kubernetes)
- Monitoring and Logging: Experience with monitoring and logging tools like DataDog, Prometheus, or Grafana
- Data Engineering Skills: Knowledge of event streaming platforms (e.g., Apache Kafka) and SQL database management
- Strong Communication and Collaboration: Excellent communication skills and the ability to work effectively in a remote, collaborative environment
Nice To Haves
- Experience with infrastructure-as-code tools like Terraform or CloudFormation.
- Familiarity with microservices architecture and RESTful API design.
- Experience leading small projects and managing stakeholders.
- Contributions to open-source projects or participation in the MLOps community.
What We Offer
- Competitive compensation
- Opportunity for equity ownership
- Private health insurance option
- Employee Resource Groups
- Fun company outings and events
- Generous PTO Allowance
- 5% Pension contribution
DailyPay does not accept and will not review unsolicited resumes from search firms.
DailyPay is committed to fostering an inclusive, equitable culture of belonging, grounded in empathy and respect, which values openness to opinions, awareness of lived experiences, fair treatment and access for all. We strive to build and develop diverse teams to create an organisation where innovation thrives, where the full potential of each person is engaged, and their views, beliefs and values are integrated into our ways of working.
We are an equal opportunities employer and welcome applications from all sections of the community.
Compensation Range: £64K - £87KSeniority level
- Seniority levelMid-Senior level
Employment type
Job function
- Job functionEngineering and Information Technology
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