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Senior ML Engineer

Open 29d

About the role

In this role, you will design, build, and operate scalable, production-grade ML systems. You’ll work at the intersection of Machine Learning Engineering, MLOps, and cloud-native infrastructure to enable the successful deployment and operation of AI solutions at scale for a leading UK grocery retailer.

You will collaborate closely with Data Scientists, Engineers, and Architects to transform ML prototypes into reliable, secure, and maintainable production systems. This role combines deep technical expertise with operational ownership, performance optimization, and engineering leadership.

SoftServe is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment regardless of race, color, religion, age, sex, nationality, disability, sexual orientation, gender identity and expression, veteran status, and other protected characteristics under applicable law. Let’s put your talents and experience in motion with SoftServe.

  • Expert-level Python skills and strong experience with modern ML frameworks and production-grade ML applications
  • Strong experience with cloud platforms such as AWS and/or Azure
  • Hands-on experience with containerization and orchestration technologies, including Docker and Kubernetes (EKS/AKS)
  • Experience with Infrastructure as Code tools, such as Terraform
  • Deep understanding of MLOps practices, including:
  • CI/CD pipelines (e.g., GitHub Actions)
  • Model versioning and experiment tracking (e.g., MLflow)
  • Workflow orchestration tools such as Airflow
  • Automated deployment, monitoring, and retraining workflows
  • Strong software engineering fundamentals, including Git, testing, code reviews, documentation, and maintainable coding practices
  • Experience implementing monitoring and observability for: Model performance tracking, Data and concept drift detection, System metrics, logging, and alerting
  • Solid understanding of data engineering fundamentals, including data pipelines, integration, transformation, and data quality processes (e.g., DBT, Kafka)

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