AWS & SageMaker MLOps Expert
3 days ago
Role: AWS & SageMaker MLOps Expert Location: Pune (Onsite) Job type: Contract/Full time Experience Level: 5+ years in DevOps/MLOps/Cloud Engineering with 3+ years specifically on AWS SageMaker and proven track record of production ML deployments at scale Certifications (Bonus): AWS Certified Machine Learning – Specialty, AWS Certified Solutions Architect (Associate/Professional) AWS SageMaker Expertise: Hands-on experience with SageMaker Unified Studio, Pipelines, Model Registry, Feature Store, Endpoints (real-time/batch), Experiments, Debugger, Clarify, and Model Monitor for comprehensive ML lifecycle management. ML Lifecycle Management: End-to-end MLOps including data preprocessing, model training, hyperparameter tuning, versioning, deployment strategies (blue/green, canary, A/B testing), monitoring, and automated retraining workflows. Programming Proficiency: Strong Python (pandas, NumPy, scikit-learn, PyTorch/TensorFlow, XGBoost), boto3 for AWS SDK, SQL for data querying, and Git/GitHub for version control and collaboration AWS Cloud & Infrastructure: Deep knowledge of AWS services: EC2, S3, Lambda, Step Functions, ECS/EKS, IAM, VPC, CloudWatch, EventBridge, Glue, Athena, and Infrastructure as Code (CloudFormation, AWS CDK, or Terraform) CI/CD & Automation: Building/deploying ML pipelines with GitHub Actions/GitLab CI, automated testing frameworks, and deployment automation with proper rollback strategies Monitoring & Observability: Experience with SageMaker Model Monitor for data quality, model drift, bias detection, and explainability (SageMaker Clarify, SHAP, LIME), CloudWatch metrics/alarms, and custom monitoring dashboards Advanced ML Operations: SageMaker Feature Store for feature management, SageMaker Automatic Model Tuning, distributed training (SageMaker Training Jobs with multi-GPU/multi-node), and model optimization techniques (quantization, pruning)
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MLOps Engineer — AWS SageMaker
1 week ago
bangalore, India Hadron Talent -Hadronfinsys Full timeMLOps Engineer — AWS SageMaker Client: A large global enterprise (name not disclosed) Location: India Work Model: 100% Remote Contract: 6 months (initial) with possibility of extension Start Date: ASAP Engagement: Full-time / Long-term contract Role Overview You will work within a global data & analytics team to design, deploy, and maintain robust ML...
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MLOps Engineer — AWS SageMaker
13 hours ago
bangalore, India Hadron Talent -Hadronfinsys Full timeMLOps Engineer — AWS SageMaker Client: A large global enterprise (name not disclosed) Location: India Work Model: 100% Remote Contract: 6 months (initial) with possibility of extension Start Date: ASAP Engagement: Full-time / Long-term contract Role Overview You will work within a global data & analytics team to design, deploy, and maintain robust ML...
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MLOps Engineer — AWS SageMaker
1 week ago
bangalore, India Hadron Talent -Hadronfinsys Full timeMLOps Engineer — AWS SageMakerClient: A large global enterprise (name not disclosed)Location: IndiaWork Model: 100% RemoteContract: 6 months (initial) with possibility of extensionStart Date: ASAPEngagement: Full-time / Long-term contractRole OverviewYou will work within a global data & analytics team to design, deploy, and maintain robust ML pipelines...
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SageMaker Administrator
2 weeks ago
bangalore, India Digivance Solutions Full timeSenior AI Engineer / SageMaker AdministratorLocation: Bangalore / Pune / Mysore / HyderabadIndustry: BankingExperience: 8+ years (3+ years relevant in AI Engineering / AWS / SageMaker)Work Mode: HybridInterview Mode: Face-to-FaceShift Timing: 10:30 AM – 8:00 PMAbout the Role We are looking for a highly skilled Senior AI Engineer / SageMaker Administrator...
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MLOPs
16 hours ago
bangalore, India Meril Full timeJob Title: MLOps Engineer Experience: Minimum 3 Years Location: Chennai Employment Type: Full-time About the Role: We are seeking an experienced MLOps Engineer with a focus on healthcare AI to join our innovative team. This role involves designing, implementing, and maintaining scalable MLOps pipelines for deploying deep learning models, including very deep...
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AWS AI/ML Engineer
2 days ago
bangalore, India Mindcraft Labs Full timeRole Description This is a hands-on engineering role focused on building and maintaining AI and ML services on AWS. You will help turn ideas and prototypes into robust, production-ready APIs and ML flows using Amazon Bedrock, Amazon SageMaker, Python, and FastAPI. Please note that the working hours for this job would be 5PM to 2AM IST . Build and maintain...
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AWS AI/ML Engineer
2 days ago
bangalore, India Mindcraft Labs Full timeRole Description This is a hands-on engineering role focused on building and maintaining AI and ML services on AWS. You will help turn ideas and prototypes into robust, production-ready APIs and ML flows using Amazon Bedrock, Amazon SageMaker, Python, and FastAPI. Please note that the working hours for this job would be 5PM to 2AM IST . Build and maintain...
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MLOps Engineer
2 weeks ago
bangalore, India Capgemini Full timeResponsibilities Experience in developing MLOps framework cutting ML lifecycle: model development, training, evaluation, deployment, monitoring including Model Governance Expert in Azure Databricks, Azure ML, Unity Catalog Hands-on experience with Azure DevOps, MLOPS CI/CD Pipelines, Python, Git, Docker Experience in developing standards and practices for...
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Generative AI Engineer
15 hours ago
bangalore, India Zimetrics Full timeMust Have: - Strong proficiency in Python and Rest APIs - Hands-on experience with AWS Bedrock (foundation models, prompt engineering, managed inference) - Practical expertise in Amazon SageMaker (training, tuning, monitoring, JumpStart) - Experience with commercial LLMs (eg. OpenAI GPT, Claude, Google Gemma) and open-source LLMs (eg. Llama, Qwen) - Good...
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MLOps Engineer
9 hours ago
bangalore, India beBeeMachineLearning Full timeUnlocking the Power of Machine Learning OperationsWe are seeking a highly skilled Senior MLOps Engineer to join our team. This role involves deploying machine learning (ML) models at scale, utilizing cloud-based infrastructure and containerization.Key Responsibilities:Design and implement efficient ML deployment pipelines using AWS services such as Lambda,...
