Genpact (NYSE: G) is a global professional services and solutions firm delivering outcomes that shape the future. Our 125,000 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.

Inviting applications for the role of Manager – MLOps

In this role, the person is responsible to design and architect scalable solutions that leverage ML algorithms, deep learning models and other AI techniques. This role must navigate successfully between the stakeholder groups, data scientists and ML Engineers and deliver deploy AI models and applications, work with the team to promote the Gen AI/AI capabilities services.

Responsibilities:

Infrastructure Design and Implementation:

Design and build scalable infrastructure for deploying and managing machine learning models in production environments.

Implement CI/CD pipelines to automate model deployment and updates.

Automation and Optimization:

Develop automation scripts and tools to streamline the ML pipeline, improving efficiency and reducing manual intervention.

Optimize models for performance, scalability, and cost-effectiveness.

Collaboration and Support:

Collaborate with cross-functional teams to understand model requirements and provide infrastructure support.

Work closely with data scientists and software engineers to ensure smooth integration of ML models into production systems.

Monitoring and Maintenance:

Implement monitoring and alerting systems to track the performance and health of deployed models.

Troubleshoot issues and perform root cause analysis to ensure the reliability and availability of ML systems.

Security and Compliance:

Ensure the security and compliance of ML systems, including data privacy and protection measures.

Stay informed about industry best practices and standards in ML Ops security.

Documentation and Training:

Document infrastructure, processes, and procedures to facilitate knowledge sharing and ensure reproducibility.

Provide training and support to stakeholders on ML Ops best practices and tools.

Qualifications we seek in you

Minimum Qualifications:

Bachelor’s degree in Computer Science, Engineering, or a related field.

Strong programming skills in languages such as Python, Java, or Scala.

Experience with cloud platforms such as AWS, Azure, or GCP.

Proficiency in containerization technologies like Docker and Kubernetes.

Knowledge of machine learning concepts and frameworks (e.g., TensorFlow, PyTorch).

Experience with CI/CD tools (e.g., Jenkins, GitLab CI) and infrastructure-as-code (e.g., Terraform).

Excellent problem-solving and analytical skills.

Strong communication and collaboration abilities.

Preferred Qualifications/skills:

Excellent analytical and problem-solving skills, with the ability to translate complex business requirements into practical AI solutions.

Effective communication and presentation skills, with the ability to articulate technical concepts to non-technical audiences.

Proven ability to work effectively in cross-functional teams and collaborate with diverse stakeholders.

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 diversity and inclusion, respect and integrity, customer focus, and innovation. Get to know us at genpact.com and on LinkedIn, X, YouTube, and Facebook.

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.