Job Description

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 \xe2\x80\x93 the relentless pursuit of a world that works better for people \xe2\x80\x93 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 Lead Consultant-ML Ops Engineer!Seeking a motivated and experienced MLOps Engineer to join our growing Generative AI team. In this role, you will be responsible for the development, deployment, and maintenance of machine learning models and pipelines, ensuring the seamless integration of AI capabilities into our product offerings.Responsibilities:
1. Collaborate with our team of data scientists, machine learning engineers, and software developers to design, develop, and deploy scalable machine learning models and pipelines for generative AI applications.
2. Implement robust, automated, and scalable ML workflows, including data pre-processing, feature engineering, model training, evaluation, and deployment.
3. Develop and maintain the infrastructure required for optimal extraction, transformation, and loading of data from various data sources using SQL and big data technologies.
4. Monitor and manage the performance and reliability of deployed machine learning models, ensuring they meet business requirements and deliver accurate and actionable insights.
5. Implement best practices for version control, testing, and continuous integration/continuous deployment (CI/CD) of machine learning models and pipelines.
6. Evaluate and adopt new ML frameworks, tools, and technologies to enhance the efficiency and effectiveness of our generative AI solutions.
7. Collaborate with cross-functional teams to identify opportunities for leveraging AI capabilities to drive business growth and innovation.
8. Provide technical expertise and guidance on MLOps best practices, as well as contribute to the development of internal tools and processes to improve overall efficiency.
Qualifications we seek in you!Minimum Qualifications
1. Bachelor\'s or Master\'s degree in Computer Science, Engineering, Mathematics, or a related field.
2. experience in MLOps, machine learning engineering, or a related field.
3. Strong knowledge of generative AI techniques, such as GANs, VAEs, and transformers, as well as experience with common machine learning frameworks, such as TensorFlow, PyTorch, or Keras.
4. Proficiency in programming languages, such as Python, Java, or C++, and experience with SQL and database management systems.
5. Experience with cloud platforms, such as AWS, GCP, or Azure, and containerization technologies, such as Docker and Kubernetes.
6. Familiarity with big data technologies, such as Hadoop, Spark, and Apache Beam, and experience with data pipeline and workflow management tools, such as Apache Airflow or Kubeflow.
7. Passion for staying up-to-date with the latest developments in AI and machine learning research, and a commitment to continuous learning and professional growth.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 and on , , , and .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.

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