MLOps Engineer

About the Role

We are looking for an experienced AWS MLOps / DevOps Engineer to design automate and optimize machine learning and data workflows on AWS. You will play a central role in building scalable secure and reliable ML infrastructure that accelerates model development and deployment across the organization.

This position is ideal for someone who combines strong AWS engineering modern DevOps practices and hands-on ML workflow experience.

Key Responsibilities

MLOps & Machine Learning Workflow Automation

• Build and maintain end-to-end ML pipelines using Amazon SageMaker Step Functions Lambda and Glue.
• Implement model lifecycle workflows: data preprocessing feature engineering model training model registry deployment and monitoring.
• Automate model deployment to real-time endpoints and batch systems.
• Establish model monitoring including data drift model drift performance metrics and automated retraining triggers.

AWS Cloud Engineering

• Design automate and maintain AWS infrastructure using AWS CloudFormation and/or Terraform.
• Build scalable data and ML environments using AWS services such as S3 ECR ECS/EKS Lambda VPC IAM and CloudWatch.
• Build Spark-based ETL pipelines using AWS Glue EMR or Spark on Kubernetes.
• Ensure compliance with AWS security best practices including IAM governance and encryption.

DevOps CI/CD & Automation

• Develop CI/CD pipelines for ML and data workflows using GitHub Actions GitLab CI Jenkins or CodePipeline.
• Implement automated testing for data validation model quality pipeline integrity and infrastructure deployments.
• Maintain logging monitoring and observability systems using CloudWatch Prometheus/Grafana or ELK.

Collaboration & Technical Leadership

• Work closely with Data Scientists to productionize notebooks scripts and models.
• Collaborate with Data Engineering to align data processing workflows with ML requirements.
• Drive best practices in automation model deployment and cloud architecture.

Qualifications :

Required Skills & Experience

Technical Expertise

• Strong hands-on experience with AWS CloudFormation for Infrastructure-as-Code.
• Deep expertise with Amazon SageMaker (training jobs pipelines model registry endpoints).
• Competency with AWS Glue and Spark for ETL and feature pipeline development.
• Strong programming skills in Python (ML workflows pipeline orchestration automation).
• Proficient with AWS Lambda for serverless ML and automation.
• Experience with building data preprocessing workflows and feature engineering pipelines.
• Strong understanding of model monitoring model drift detection and model productionisation.

DevOps & Cloud

• Expertise in CI/CD for ML (GitHub Actions GitLab Jenkins CodePipeline).
• Familiarity with Docker and container orchestration (ECS EKS Fargate).
• Strong understanding of AWS networking IAM security best practices and high-availability design.

Soft Skills

• Strong communication skills and ability to collaborate with cross-functional teams.
• Ability to lead technical discussions and influence architectural decisions.
• Problem-solving mindset with passion for automation and scalability.

Preferred Qualifications

• Experience with MLflow Kubeflow Airflow or Step Functions for pipeline orchestration.
• Experience with Glue Studio Glue Workflows or EMR for large-scale Spark processing.
• AWS Certifications (MLOps / DevOps Engineer / Solutions Architect / ML Specialty).
• Knowledge of data governance lineage and compliance frameworks.
• Knowledge of security best practices

Nice to have

• Finance Sector customer experience such as banking insurance etcetera
• Understanding of regulatory constraints auditing requirements compliance and secure data-handling patterns.

Additional Information :

Why Version 1

At Version 1 we believe in providing our employees with a comprehensive benefits package that prioritises their wellbeing professional growth and financial stability.

• Share in our success with our Quarterly Performance-Related Profit Share Scheme where employees collectively benefit from a share of our companys profits.
• Strong Career Progression & mentorship coaching through our Strength in Balance & Leadership schemes with a dedicated quarterly Pathways Career Development programme.
• Flexible/remote working Version 1 is tremendously understanding of life events and peoples individual circumstances and offer flexibility to help achieve a healthy work life balance.
• Financial Wellbeing initiatives including; Pension Private Healthcare Cover Life Assurance Financial advice and an Employee Discount scheme.
• Employee Wellbeing schemes including Gym Discounts Bike to Work Fitness classes Mindfulness Workshops Employee Assistance Programme and much more. Generous holiday allowance enhanced maternity/paternity leave marriage/civil partnership leave and special leave policies.
• Educational assistance incentivised certifications and accreditations including AWS Microsoft Oracle and Red Hat.
• Reward schemes including Version 1s Annual Excellence Awards & Call-Out platform.
• Environment Social and Community First initiatives allow you to get involved in local fundraising and development opportunities as part of fostering our diversity inclusion and belonging schemes.

And many more exciting benefits drop us a note to find out more.

Remote Work :

No

Employment Type :

Full-time