Lead Consultant- ML Ops Engineer

Genpact (NYSE: G) is a global professional services and solutions firm delivering outcomes that shape the future. Our 125000 people across 30 countries are driven by our innate curiosity entrepreneurial agility and desire to create lasting value for clients. Powered by our purpose the relentless pursuit of a world that works better for people we serve and transform leading enterprises including the Fortune Global 500 with our deep business and industry knowledge digital operations services and expertise in data technology and AI.

We are inviting applications for the role of Lead Consultant ML Ops Engineer!
we are looking for a candidate 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 cloud engineer shall perform duties on tasks that require expertise in AWS/system/processor architecture client/server architecture operating systems software applications network protocols routers switches remote access servers and firewalls.
We are seeking an experienced and proactive DevOps Engineer with handson experience.
As a DevOps Engineer you will play a critical role in automating and optimizing our software development deployment and infrastructure processes. You will work closely with crossfunctional teams including developers system administrators and IT operations to ensure the smooth and efficient delivery of software products.
Core ML Ops work experience in ML Ops Engineer /Insurance; Second preference data analytics experience coupled with hands on technical skills Python AIMLSQL and MS Dynamics 365.
Work location: India(Noida)

Responsibilities
Design develop and implement ML/LLM pipelines for generative AI models encompassing data ingestion preprocessing 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 signoff 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 costefficiency 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 nontechnical stakeholders about the health and performance of generative AI models.

Qualifications we seek in you!
Minimum Qualifications
Masters or Bachelors in engineering BE/B Tech BCA MCA BSc/MSc
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.

Preferred Qualifications:
Proven experience in ML Ops LLM Ops or related roles with handson 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 problemsolving skills.
Ability to work independently and as part of a team.
Passion for Generative AI and its potential to revolutionize various industries.

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. For more information visit www.genpact . Follow us on Twitter Facebook LinkedIn and YouTube.

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.