MLOps Engineer

MLOps Engineer📍 Location: Fully Remote (Turkey-based, aligned with UK working hours)📄 Contract: Until end of February 2026 (initial, with high likelihood of extension)🚀 Start Date: ASAP🌍 About UsCressoft is a trusted IT consultancy firm in the UK, operating since 2011. We deliver impactful projects and provide top-tier tech talent to our clients. We’re proud to be the exclusive offshore talent supplier for a leading UK retail digital transformation programme — an exciting opportunity to join a team that values expertise and innovation.💼 About the ClientYou’ll be working with one of the UK’s largest and most respected retail organisations, known for its diverse portfolio of brands across grocery, e-commerce, furniture, loyalty, and banking. Their technology division employs over 3,000 engineers and operates like a startup — fast-paced, innovative, and focused on in-house development.🧠 About the RoleYou’ll be part of MLOps Engineering squads working on Ad-tech, interpreting and following architectural and engineering principles, operating frameworks, and new and improved technology and solutions. With your technical craft, curiosity, and experimentation, you’ll use your judgement to apply specific techniques to deliver focused outcomes that support customers.We build AI/ML data products that underpin key commercial decisions, bring intelligent automation to operational systems, and power customer-facing applications through microservices.As an MLOps Engineer, you’ll support these products from inception — working across the full data ecosystem, from building CI/CD pipelines for ML models to developing APIs for real-time model outputs.🛠️ Key ResponsibilitiesDesign, implement, and maintain scalable ML model deployment pipelines (CI/CD for ML).Build infrastructure to monitor model performance, data drift, and other key metrics in production.Develop and maintain tools for model versioning, reproducibility, and experiment tracking.Optimize model serving infrastructure for latency, scalability, and cost.Automate the end-to-end ML workflow — from data ingestion to model training, testing, deployment, and monitoring.Collaborate with data scientists to ensure production-ready models.Implement security, compliance, and governance practices for ML systems.Support troubleshooting and incident response for deployed ML systems.✅ Required QualificationsStrong programming skills in Python; experience with ML libraries such as Snowpark, PySpark, or PyTorch.Experience with Docker and orchestration tools like Airflow or Astronomer.Familiarity with cloud platforms (AWS, Azure) and ML services (e.g., SageMaker, Vertex AI).Experience with CI/CD pipelines and automation tools like GitHub Actions.Understanding of monitoring and logging tools (NewRelic, Grafana).🌟 Preferred QualificationsPrior experience deploying ML models in production environments.Knowledge of infrastructure-as-code tools like Terraform or CloudFormation.Familiarity with model interpretability and responsible AI practices.Experience with feature stores and model registries.💬 Work ArrangementFully Remote – Work hours: 9 AM to 5 PM UK time for seamless collaboration.Communication Tools: Microsoft Teams and Slack.