Job Type: Full-time

Remote: Hybrid

About Position:We are seeking an experienced AWS Sage Maker Engineer to design and build scalable MLOps platforms and machine learning pipelines on AWS. The role focuses on enabling end-to-end ML lifecycle management including model development, deployment, monitoring, and automation. The ideal candidate will have strong expertise in Sage Maker, cloud-native architecture, and Dev Ops practices, along with the ability to collaborate with data science teams to productionize ML use cases efficiently.Role : AWS Sage Maker EngineerLocation: All Persistent LocationExperience: 8-12 yearsJob Type: Full Time EmploymentWhat You'll Do:Design and implement end-to-end MLOps pipelines on Amazon Sage Maker for training, validation, deployment, and monitoringBuild Dev Ops automation to provision and manage ML infrastructure across environmentsDevelop Python-based tools and frameworks to standardize ML workflows and platform operationsImplement CI/CD pipelines for ML models, feature pipelines, and Sage Maker jobsAutomate model packaging, versioning, promotion, and rollback across Dev/Test/ProdEnforce security, governance, and compliance controls for ML platforms and data accessOptimize Sage Maker workloads for performance, scalability, and cost efficiencyIntegrate Sage Maker with AWS services such as S3, IAM, Cloud Watch, Event Bridge, and ECRImplement monitoring and alerting for model performance, drift, failures, and infrastructure healthCollaborate with data science and engineering teams to productionize ML use casesTroubleshoot complex platform, pipeline, and deployment issues in distributed ML systemsDrive platform best practices, documentation, and continuous improvement initiativesExpertise You'll Bring:8-12 years of hands-on experience in Dev Ops, MLOps, or ML platform engineeringStrong expertise with Amazon Sage Maker for building and operating ML pipelinesAdvanced proficiency in Python for automation, pipeline development,



and toolingDeep experience with AWS services supporting ML platforms and CI/CDProven experience building enterprise-scale Dev Ops and MLOps automation frameworksStrong understanding of CI/CD, Infrastructure as Code, and cloud-native architecturesExperience securing ML platforms using IAM, encryption, and network isolationHands-on exposure to model monitoring, drift detection, and lifecycle managementExperience optimizing cloud resources for cost, scalability, and reliabilityStrong analytical and problem-solving skills in distributed environmentsAbility to collaborate across data science, engineering, security, and operations teamsOwnership mindset with the ability to drive platforms end-to-endBenefits:Competitive salary and benefits packageCulture focused on talent development with quarterly growth opportunities and company-sponsored higher education and certificationsOpportunity to work with cutting-edge technologiesEmployee engagement initiatives such as project parties, adaptable work hours, and Long Service awardsAnnual health check-upsInsurance coverage: group term life, personal accident, and Mediclaim hospitalization for self, spouse, two children, and parentsValues-Driven, People-Centric & Inclusive Work Environment:Persistent is dedicated to fostering diversity and inclusion in the workplace. We invite applications from all qualified individuals, including those with disabilities, and regardless of gender or gender preference. We welcome diverse candidates from all backgrounds.We support hybrid work and flexible hours to fit diverse lifestyles.Our office is accessibility-friendly, with ergonomic setups and assistive technologies to support employees with physical disabilities.If you are a person with disabilities and have specific requirements, please inform us during the application process or at any time during your employmentLet's unleash your full potential at Persistent - "Persistent is an Equal Opportunity Employer and prohibits discrimination and harassment of any kind."

📌 Aws sagemaker engineer (Pune)
🏢 Persistent Systems
📍 Pune