MLOps Engineer at Version 1 Accelerate

Pune, maharashtra, India -

Full Time

Start Date

Immediate

Expiry Date

24 May, 26

Salary

0.0

Posted On

23 Feb, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

AWS, MLOps, DevOps, Amazon SageMaker, Step Functions, Lambda, Glue, CloudFormation, Terraform, S3, ECR, ECS/EKS, VPC, IAM, CloudWatch, Python

Industry

IT Services and IT Consulting

Description

Company Description Version 1 has celebrated over 29 years in Technology Services and continues to be trusted by global brands to deliver solutions that drive customer success. Our expertise enables our customers to navigate the rapidly changing Digital-First world we live in. We foster strong partnerships with leading technology giants including Microsoft, AWS, Oracle, Red Hat, OutSystems, Snowflake, ensuring that our customers are provided with the highest quality solutions and services. We’re an award-winning employer reflecting how our employees are at the very heart of Version 1 and what we do: UK & Ireland's premier AWS, Microsoft & Oracle partner 3300+ strong, €350/£300m revenue business 10+ years as a Great Place to Work in Ireland & UK Best Workplace for Women in the UK & Ireland by GPTW Best Workplace for Wellbeing in the UK by GPTW We’re a core values driven company, we hire people who share our values, and we reward those who display and foster them, it’s deeply embedded within our DNA. Invest in us and we’ll invest in you! Job Description 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 company's 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 people’s 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 1’s 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. Department: Digital, Data and Cloud

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Responsibilities

The role involves designing, automating, and optimizing machine learning and data workflows on AWS, focusing on building scalable, secure, and reliable ML infrastructure. Key tasks include building end-to-end ML pipelines using SageMaker, implementing model lifecycle workflows, and automating model deployment and monitoring.