Persistent Systems
Website:
persistent.com
Job details:
About Persistent
We are an AI-led, platform-driven Digital Engineering and Enterprise Modernization partner, combining deep technical expertise and industry experience to help our clients anticipate what’s next. Our offerings and proven solutions create a unique competitive advantage for our clients by giving them the power to see beyond and rise above. We work with many industry-leading organizations across the world, including 20 Fortune 50 companies and 4 of the 5 top banks in both the US and India, and numerous innovators across the healthcare ecosystem.
Our disruptor’s mindset, commitment to client success, and agility to thrive in the dynamic environment have enabled us to sustain our growth momentum. Persistent has been recognized across top industry platforms for innovation, leadership, and inclusion. We reported $1,654.4M FY26 revenue with 17.4% Y-o-Y growth. We have delivered 24 sequential quarters of growth with $436.0M in Q4 FY26 revenue, up 3.2% Q-o-Q and 16.2% Y-o-Y growth. Our 27,500+ global team members, located in 18 countries, have been instrumental in helping the market leaders transform their industries. We have been recognized as the Fastest Growing IT Services Brand Globally in the 2026 Brand Finance IT Services 25 Report. We named a Leader in the Everest Group Private Equity (PE) Services PEAK Matrix® Assessment 2026 and Software Product Engineering PEAK Matrix® Assessment 2026.
About Position
We are seeking an experienced AWS SageMaker 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 SageMaker, cloud-native architecture, and DevOps practices, along with the ability to collaborate with data science teams to productionize ML use cases efficiently.
- Role: AWS SageMaker Engineer
- Location: All Persistent Location
- Experience: 8-12 years
- Job Type: Full Time Employment
- Mandatory Mention 3 skills: AWS Sage maker, Machine Learning
What You'll Do
- Design and implement end-to-end MLOps pipelines on Amazon SageMaker for training, validation, deployment, and monitoring
- Build DevOps automation to provision and manage ML infrastructure across environments
- Develop Python-based tools and frameworks to standardize ML workflows and platform operations
- Implement CI/CD pipelines for ML models, feature pipelines, and SageMaker jobs
- Automate model packaging, versioning, promotion, and rollback across Dev/Test/Prod
- Enforce security, governance, and compliance controls for ML platforms and data access
- Optimize SageMaker workloads for performance, scalability, and cost efficiency
- Integrate SageMaker with AWS services such as S3, IAM, CloudWatch, Event Bridge, and ECR
- Implement monitoring and alerting for model performance, drift, failures, and infrastructure health
- Collaborate with data science and engineering teams to productionize ML use cases
- Troubleshoot complex platform, pipeline, and deployment issues in distributed ML systems
- Drive platform best practices, documentation, and continuous improvement initiatives
Expertise You'll Bring
- 8-12 years of hands-on experience in DevOps, MLOps, or ML platform engineering
- Strong expertise with Amazon SageMaker for building and operating ML pipelines
- Advanced proficiency in Python for automation, pipeline development, and tooling
- Deep experience with AWS services supporting ML platforms and CI/CD
- Proven experience building enterprise-scale DevOps and MLOps automation frameworks
- Strong understanding of CI/CD, Infrastructure as Code, and cloud-native architectures
- Experience securing ML platforms using IAM, encryption, and network isolation
- Hands-on exposure to model monitoring, drift detection, and lifecycle management
- Experience optimizing cloud resources for cost, scalability, and reliability
- Strong analytical and problem-solving skills in distributed environments
- Ability to collaborate across data science, engineering, security, and operations teams
- Ownership mindset with the ability to drive platforms end-to-end
Benefits
- Competitive salary and benefits package
- Culture focused on talent development with quarterly growth opportunities and company-sponsored higher education and certifications
- Opportunity to work with cutting-edge technologies
- Employee engagement initiatives such as project parties, flexible work hours, and Long Service awards
- Annual health check-ups
- Insurance coverage: group term life, personal accident, and Mediclaim hospitalization for self, spouse, two children, and parents
Values-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 employment
Let’s unleash your full potential at Persistent - persistent.com/careers
“Persistent is an Equal Opportunity Employer and prohibits discrimination and harassment of any kind.”
AWS Sage maker, Machine Learning
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