Senior MLOps Engineer
Senior MLOps Engineer
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Job Description
Job Description
Senior MLOps Engineer
Location: UK (Hybrid)
We are seeking an experienced Senior MLOps Engineer to join a leading digital engineering team working on cuttingedge 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 handson 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 cloudbased 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.
- Handson development experience using Python particularly with TensorFlow PyTorch scikitlearn boto3 and the Python Data Science stack (pandas numpy etc..
- Strong analytical and problemsolving skills with the ability to work with largescale 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 largescale 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
Required Experience:
Senior IC
Employment Type
Full-Time
