Assistant Manager, ML Ops Engineer

Ready to build the future with AI
At Genpact we dont just keep up with technologywe set the pace. AI and digital innovation are redefining industries and were leading the charge. Genpacts AI Gigafactory our industry-first accelerator is an example of how were scaling advanced technology solutions to help global enterprises work smarter grow faster and transform at scale. From large-scale models to agentic AI our breakthrough solutions tackle companies most complex challenges.
If you thrive in a fast-moving innovation-driven environment love building and deploying cutting-edge AI solutions and want to push the boundaries of whats possible this is your moment.
Genpact (NYSE: G) is an advanced technology services and solutions company that delivers lasting value for leading enterprises globally. Through our deep business knowledge operational excellence and cutting-edge solutions we help companies across industries get ahead and stay ahead. Powered by curiosity courage and innovation our teams implement data technology and AI to create tomorrow today. Get to know us at and on LinkedIn X YouTube and Facebook.

Inviting applications for the role of Assistant Manager ML Ops Engineer!
We are seeking a highly skilled and experienced ML Ops / LLM Ops Engineer to join our team. You will play a crucial role in building and maintaining the infrastructure and pipelines for our cutting-edge Generative AI applications working closely with the Generative AI Full Stack Architect. Your expertise in automating and streamlining the ML lifecycle will be instrumental in ensuring the efficiency scalability and reliability of our Generative AI models in production.
Responsibilities
Design develop and implement ML/LLM pipelines for generative AI models encompassing data ingestion pre-processing training deployment and monitoring.
MLOps Support and Maintenance on ML Platforms Dataiku/Sagemaker
Apply understanding of Dataiku Govern functionalities including item and artifact management workflow control and sign-off processes.
Using best practices for data governance and model accountability within the MLOps lifecycle.
Automate ML tasks across the model lifecycle leveraging tools like GitOps CI/CD pipelines and containerization technologies (e.g. Docker Kubernetes).
Implement version control CI/CD pipelines and containerization techniques to streamline ML and LLM workflows.
Design and implement monitoring and alerting systems to track model performance data drift and other key metrics.
Conduct ground truth analysis to evaluate the accuracy and effectiveness of LLM outputs compared to known correct data.
Work closely with infrastructure and DevOps teams to provision and manage resources for ML and LLM development and deployment.
Develop and maintain robust monitoring and alerting systems for generative AI models in production ensuring proactive identification and resolution of issues.
Collaborate with the Generative AI Full Stack Architect and other engineers to optimize model performance and resource utilization.
Manage and maintain cloud infrastructure (e.g. AWS Azure) for ML workloads ensuring cost-efficiency and scalability.
Stay up to date on the latest advancements in MLOps and incorporate them into our platform and processes.
Communicate effectively with technical and non-technical stakeholders about the health and performance of generative AI models.
Qualifications we seek in you!
Minimum Qualifications
Bachelors degree in computer science Data Science Engineering or a related field or equivalent experience.
Experience in MLOps or related areas such as DevOps data engineering or ML infrastructure.
Knowledge of best practices for data governance and model accountability within the MLOps lifecycle.
Covered these Dataiku Certifications: ML Practitioner Certificate Advanced Designer Certificate and MLOps Practitioner Certificate.
Proven experience in ML Ops LLM Ops or related roles with hands-on experience deploying and managing machine learning and large language model pipelines 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).
Excellent communication collaboration and problem-solving skills.
Ability to work independently and as part of a team.
Passion for Generative AI and its potential to revolutionize various industries.

Why join Genpact
Lead AI-first transformation Build and scale AI solutions that redefine industries
Make an impact Drive change for global enterprises and solve business challenges that matter
Accelerate your careerGain hands-on experience world-class training mentorship and AI certifications to advance your skills
Grow with the best Learn from top engineers data scientists and AI experts in a dynamic fast-moving workplace
Committed to ethical AI Work in an environment where governance transparency and security are at the core of everything we build
Thrive in a values-driven culture Our courage curiosity and incisiveness - built on a foundation of integrity and inclusion - allow your ideas to fuel progress
Come join the 140000 coders tech shapers and growth makers at Genpact and take your career in the only direction that matters: Up.
Lets build tomorrow together.
Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race color religion or belief sex age national origin citizenship status marital status military/veteran status genetic information sexual orientation gender identity physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values respect and integrity customer focus and innovation.
Furthermore please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a starter kit paying to apply or purchasing equipment or training.