Lead Consultant-ML Ops Engineer
5 months ago
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 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.
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