MLOps Engineer

Responsibilities

• Design, build, and maintain scalable MLOps pipelines for ML model development, deployment, and monitoring.
• Develop CI/CD pipelines to automate model and application deployment across environments.
• Build and manage data and ML workflows using tools such as Python, Airflow/Composer, Git, and cloud platforms.
• Deploy and manage ML models using platforms such as Vertex AI or equivalent ML platforms.
• Implement model monitoring, performance tracking, logging, alerting, and retraining workflows.
• Work closely with Data Scientists, Data Engineers, and Software Engineers to productionize ML models.
• Develop APIs and services to integrate ML models with downstream applications.
• Ensure solutions are scalable, reliable, secure, and maintainable.
• Troubleshoot production issues and optimize ML pipelines for performance and reliability.
• Follow software engineering best practices including code reviews, testing, documentation, and version control.
  
  

Requirements

• 4 to 7 years of experience as ML Engineer
• Strong Python programming and software engineering skills.
• Hands-on MLOps experience with production ML pipelines.
• Experience building CI/CD pipelines and working with Git/GitHub.
• Strong understanding of ML model lifecycle management, deployment, monitoring, and automation.
• Experience with REST APIs/microservices and containerization such as Docker.
• Ability to work effectively with Data Science and Data Engineering teams.
  
  

Nice to have

• Nice to have experience with GCP, preferably Vertex AI, BigQuery, Cloud Storage, and Composer/Airflow.
  
  

We offer

• Opportunity to work on bleeding-edge projects
• Work with a highly motivated and dedicated team
• Competitive salary
• Flexible schedule
• Benefits package - medical insurance, sports
• Corporate social events
• Professional development opportunities
• Well-equipped office
  
  

About Us

Grid Dynamics (NASDAQ: GDYN) is a leading provider of technology consulting, platform and product engineering, AI, and advanced analytics services. Fusing technical vision with business acumen, we solve the most pressing technical challenges and enable positive business outcomes for enterprise companies undergoing business transformation. A key differentiator for Grid Dynamics is our 8 years of experience and leadership in enterprise AI, supported by profound expertise and ongoing investment in data, analytics, cloud & DevOps, application modernization and customer experience. Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.

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