ML Operation Engineer

In this role you will be reporting to Head – Product & Delivery Management, you will be responsible to Identify, propose, and implements innovative technology, software and/or solutions by contributing with own ideas. Works independently as a member of an R&D team.

Responsibilities:-

• Deploy and maintain ML models in kubernetes (AKS or OpenShift).
• Work closely with the ML team, integration team(s) and the cloud administrators to deploy and integrate ML services into a wide range of products.
• Work towards building a MLOps platform for automated deployment of models.
• Deploy data and ml pipelines in Azure ML pipelines using MLOPs tools.
• Optimizing and maintaining current pipelines for data extraction and model deployment.
• Setup logging, monitoring of machine learning models in production and create end to end automated ml training pipelines.
• Work closely with the ML team to plan, build, maintain, and improve an end- to-end MLOps platform on top of KubeFlow for research, model training, logging and model serving.

Qualification And Experience:-

• BE / B Tech/ Computer Science/EC/EEE.
• Minimum 0-1 Years of experience.
• Experience in Git, Docker, Kubernetes, Helm, Kubectl.
• Workflow orchestrations tools like Apache Airflow, Prefect, MetaFlow, Luigi.
• Machine learning frameworks e.g., PyTorch, TensorFlow, ONNX.
• Model serving in ML and working with frameworks like TensorFlow Serving, TorchServe, KFServing, Seldon, BentoML etc.

Location:-

• Bangalore, India.

Company Overview:-

ABB is a leading global technology company that energizes the transformation of society and industry to achieve a more productive, sustainable future. By connecting software to its electrification, robotics, automation and motion portfolio, ABB pushes the boundaries of technology to drive performance to new levels. With a history of excellence stretching back more than 130 years, ABB’s success is driven by about 105,000 talented employees in over 100 countries.