MLOps Engineer

Grid Dynamics; Bengaluru; Presencial; INR 1 500 000 - 3 500 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Competitive salary

Flexible schedule

Benefits package - medical insurance,

Sports

Professional development opportunities

Well-equipped office

Corporate social events

Resumo da oferta

Grid Dynamics is seeking a skilled ML Engineer in Bengaluru to design, build, and maintain scalable MLOps pipelines for model development, deployment, and monitoring. You will develop CI/CD pipelines to automate model and application deployment across environments and collaborate with Data Scientists, Data Engineers, and Software Engineers to productionize ML models.

You will build data and ML workflows using Python, Airflow/Composer, Git, and cloud platforms, deploy models on Vertex AI or

Qualificações

• 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.

Responsabilidades

• 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 Python, Airflow/Composer, Git, and cloud platforms.
• Deploy and manage ML models using 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.

Conhecimentos

Python programming

Software engineering

MLOps experience

CI/CD pipelines

Team collaboration

Ferramentas

Git/GitHub

Airflow/Composer

Docker

REST APIs

Cloud platforms

Descrição da oferta de emprego

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.

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.