Machine Learning(Ops) - Engineer

Job Description

Be part of the solution at Technip Energies and embark on a one-of-a-kind journey. You will be helping to develop cutting-edge solutions to solve real-world energy problems.

About us:

Technip Energies is a global technology and engineering powerhouse. With leadership positions in LNG, hydrogen, ethylene, sustainable chemistry, and CO2 management, we are contributing to the development of critical markets such as energy, energy derivatives, decarbonization, and circularity. Our complementary business segments, Technology, Products and Services (TPS) and Project Delivery, turn innovation into scalable and industrial reality.

Through collaboration and excellence in execution, our 17,000+ employees across 34 countries are fully committed to bridging prosperity with sustainability for a world designed to last.

About the role:

We are currently seeking a Machine Learning (Ops) - Engineer, to join our Digi team based in Noida.

Key Responsibilities:

• ML Pipeline Development and Automation: Design, build, and maintain end-to-end AI/ML CI/CD pipelines using Azure DevOps and leveraging Azure AI Stack (e.g., Azure ML, AI Foundry …) and Dataiku
• Model Deployment and Monitoring: Deliver tooling to deploy AI/ML products into production, ensuring they meet performance, reliability, and security standards. Implement and maintain a transversal monitoring solutions to track model performance, detect drift, and trigger retraining when necessary
• Collaboration and Support: Work closely with data scientists, AI/ML engineers, and platform team to ensure seamless integration of products into production. Provide technical support and troubleshooting for AI/ML pipelines and infrastructure, particularly in Azure and Dataiku environments
• Operational Excellence : Define and implement MLOps best practices with a strong focus on governance, security, and quality, while monitoring performance metrics and cost-efficiency to ensure continuous improvement and delivering optimized, high-quality deployments for Azure AI services and Dataiku
• Documentation and Reporting: Maintain comprehensive documentation of AI/ML pipelines, and processes, with a focus on Azure AI and Dataiku implementations. Provide regular updates to the AI Platform Lead on system status, risks, and resource needs
  
  
  

About you:

• Proven track record of experience in MLOps, DevOps, or related roles
• Strong knowledge of machine learning workflows, data analytics, and Azure cloud
• Hands-on experience with tools and technologies such as Dataiku, Azure ML, Azure AI Services, Docker, Kubernetes, and Terraform
• Proficiency in programming languages such as Python, with experience in ML and automation libraries (e.g., TensorFlow, PyTorch, Azure AI SDK …)
• Expertise in CI/CD pipeline management and automation tools using Azure DevOps
• Familiarity with monitoring tools and logging frameworks
• Catch this opportunity and invest in your skills development, should your profile meet these requirements.
  
  
  

Additional attributes:

• A proactive mindset with a focus on operationalizing AI/ML solutions to drive business value
• Experience with budget oversight and cost optimization in cloud environments.
• Knowledge of agile methodologies and software development lifecycle (SDLC).
• Strong problem-solving skills and attention to detail
  
  
  

Work Experience: 3-5 years of experience in MLOps

Minimum Education: Advanced degree (Master’s or PhD preferred) in Computer Science, Data Science, Engineering, or a related field.

What’s next?

Once receiving your application, our Talent Acquisition professionals will screen and match your profile against the role requirements. We ask for your patience as the team completes the volume of applications with reasonable timeframe. Check your application progress periodically via personal account from created candidate profile during your application.

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