Lead Consultant - AL ML Ops
Genpact
5 - 10 years
Bengaluru
Posted: 29/11/2024
Job Description
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 Genpact is a global professional services firm delivering digital transformation by putting digital and data to work to create competitive advantage.
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.About Company
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