Senior MLOps Engineer
| Posting date: | 18 March 2025 |
|---|---|
| Hours: | Full time |
| Closing date: | 17 April 2025 |
| Location: | London |
| Company: | Willing Care Recruitment Limited |
| Job type: | Permanent |
| Job reference: | 1262972147 |
Summary
Senior MLOps Engineer
Location: UK (Hybrid)
We are seeking an experienced Senior MLOps Engineer to join a leading digital engineering team, working on cutting-edge AI and machine learning projects. In this role, you will be responsible for architecting and developing software and pipelines to streamline the algorithm development lifecycle, from data curation to integration and deployment.
You will work closely with ML development teams to create robust CI/CD pipelines, build data engineering tools, and develop visualisation dashboards to monitor model performance and data drift.
Ideal Candidate Profile: We are looking for individuals with a strong background in data and MLOps, hands-on experience in developing complex data solutions, and a passion for automation within an Agile environment. The ideal candidate will have expertise in deploying ML models in production, working with cloud-based infrastructure, and implementing robust data pipelines.
Technical Skills & Experience:
- Proven experience deploying and managing ML models in production, particularly on AWS.
- Strong expertise in Amazon SageMaker (SageMaker Pipelines, Endpoints, Batch Transformation/Inference, SageMaker Studio).
- Experience with AWS MLOps tools: IAM, S3, Lambda, Step Functions, Athena/Glue, CodePipeline.
- Proficiency in container orchestration using CloudFormation, Terraform, Docker, and Kubernetes.
- Hands-on development experience using Python, particularly with TensorFlow, PyTorch, scikit-learn, boto3, and the Python Data Science stack (pandas, numpy, etc.).
- Strong analytical and problem-solving skills, with the ability to work with large-scale, complex datasets.
- Experience in automation, CI/CD, and Agile development environments.
Key Responsibilities:
- Architect and develop software solutions to support AI technologies that enhance user experiences.
- Build and maintain CI/CD pipelines for machine learning model infrastructure.
- Design and develop data engineering tools for managing, storing, and querying large-scale datasets.
- Create data and metric visualisation tools, including web UI dashboards for monitoring model performance.
- Deploy and productionise ML models on AWS, ensuring scalability and efficiency.
- Automate and streamline machine learning workflows using cloud technologies.
Reference: WILL118706/MB
INDIT