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ML Engineer Lead Consultant

1 week ago

Noida, Uttar Pradesh, India Genpact Full time
Job Description:

Genpact is a global professional services and solutions firm delivering outcomes that shape the future. With 125,000+ people across 30+ countries, we are driven by our innate curiosity, entrepreneurial agility, and desire to create lasting value for clients. Our purpose - the relentless pursuit of a world that works better for people - guides us as we serve and transform leading enterprises, including Fortune Global 500 companies, with our deep business and industry knowledge, digital operations services, and expertise in data, technology, and AI.

We are seeking an experienced Lead Consultant - ML Ops Engineer to perform duties such as cloud readiness assessments, AWS architecture design, system evaluation, system analysis, AWS Infrastructure Operations, Optimization and Maintenance, Change and Configuration Management Support, Release, Control and Validation of Cloud Infrastructure Deployment and Migration, and infrastructure assessment. The ideal candidate will have hands-on experience with tasks requiring expertise in AWS/system/processor architecture, client/server architecture, operating systems, software applications, network protocols, routers, switches, remote access servers, and firewalls.

The successful candidate will play a critical role in automating and optimizing our software development, deployment, and infrastructure processes. They will work closely with cross-functional teams, including developers, system administrators, and IT operations, to ensure the smooth and efficient delivery of software products. Key responsibilities include designing, developing, and implementing ML/LLM pipelines for generative AI models, encompassing data ingestion, pre-processing, training, deployment, and monitoring.

We are looking for an individual with proven experience in ML Ops, LLM Ops, or related roles, with hands-on experience deploying and managing machine learning and large language model pipelines. The ideal candidate will have expertise in cloud platforms (e.g., AWS, Azure) for ML workloads, strong understanding of CI/CD principles, and containerization technologies like Docker and Kubernetes. Familiarity with monitoring and alerting tools for ML systems (e.g., Prometheus, Grafana) is also desirable.