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For Employers

MLOps Engineer

Name: Jobpe
Address: T-Hub, Plot No 1/C, Sy No 83/1, Raidurgam panmaktha, Knowledge City Rd, Hyderabad, Telangana, 500081, IN
Telephone: +91-83339-09630
Price range: Free

Trispoke Managed Services Pvt. Ltd.

8 years

0 Lacs

noida uttar pradesh india

Posted:1 day ago| Platform:

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Skills Required

ml aws airflow apache spark kubernetes automation data engineering design training inference model etl docker testing drift monitoring governance versioning tracking devops pipeline orchestration redshift workflow python tensorflow pytorch git github linux scripting troubleshooting development learning

Work Mode

On-site

Job Type

Full Time

Job Description

Role & ResponsibilitiesWe are looking for a Senior MLOps Engineer with 8+ years of experience building and managing production-grade ML platforms and pipelines. The ideal candidate will have strong expertise across AWS, Airflow/MWAA, Apache Spark, Kubernetes (EKS), and automation of ML lifecycle workflows. You will work closely with data science, data engineering, and platform teams to operationalize and scale ML models in production.

Key Responsibilities

Design and manage cloud-native ML platforms supporting training, inference, and model lifecycle automation.
Build ML/ETL pipelines using Apache Airflow / AWS MWAA and distributed data workflows using Apache Spark (EMR/Glue).
Containerize and deploy ML workloads using Docker, EKS, ECS/Fargate, and Lambda.
Develop CI/CT/CD pipelines integrating model validation, automated training, testing, and deployment.
Implement ML observability: model drift, data drift, performance monitoring, and alerting using CloudWatch, Grafana, Prometheus.
Ensure data governance, versioning, metadata tracking, reproducibility, and secure data pipelines.
Collaborate with data scientists to productionize notebooks, experiments, and model deployments.

Ideal Candidate

8+ years in MLOps/DevOps with strong ML pipeline experience.
Strong hands-on experience with AWS:
Compute/Orchestration: EKS, ECS, EC2, Lambda
Data: EMR, Glue, S3, Redshift, RDS, Athena, Kinesis
Workflow: MWAA/Airflow, Step Functions
Monitoring: CloudWatch, OpenSearch, Grafana
Strong Python skills and familiarity with ML frameworks (TensorFlow/PyTorch/Scikit-learn).
Expertise with Docker, Kubernetes, Git, CI/CD tools (GitHub Actions/Jenkins).
Strong Linux, scripting, and troubleshooting skills.
Experience enabling reproducible ML environments using Jupyter Hub and containerized development workflows.

Education

Master’s degree in Computer Science, Machine Learning, Data Engineering, or related field.

Perks, Benefits and Work Culture

Competitive Salary Package
Generous Leave Policy
Flexible Working Hours
Performance-Based Bonuses
Health Care Benefits

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MLOps Engineer