KPMG

Senior - Dev-HC-BE

Job Description

About KPMG in India

KPMG entities in India are professional services firm(s). These Indian member firms are affiliated with KPMG International Limited. KPMG was established in India in August 1993. Our professionals leverage the global network of firms, and are conversant with local laws, regulations, markets and competition. KPMG has offices across India in Ahmedabad, Bengaluru, Chandigarh, Chennai, Gurugram, Jaipur, Hyderabad, Jaipur, Kochi, Kolkata, Mumbai, Noida, Pune, Vadodara and Vijayawada. 

KPMG entities in India offer services to national and international clients in India across sectors. We strive to provide rapid, performance-based, industry-focused and technology-enabled services, which reflect a shared knowledge of global and local industries and our experience of the Indian business environment.

As an ML Engineer, you will be responsible for deploying, managing, and optimizing AI/ML models in production environments. You will work closely with data scientists, software engineers, and IT teams to ensure the seamless integration and operation of AI/ML solutions. Your role will be crucial in operationalizing AI models, ensuring they are scalable, reliable, and deliver value to the business.

Responsibilities:
• Design, implement, and maintain end-to-end MLOps pipelines for deploying machine learning models into production.
• Collaborate with data scientists to understand model requirements and ensure smooth deployment and integration.
• Develop and manage infrastructure for model training, validation, deployment, monitoring, and retraining.
• Implement CI/CD pipelines to streamline the deployment and updates of AI/ML models.
• Ensure the scalability, reliability, and performance of deployed models through continuous monitoring and optimization.
• Utilize containerization and orchestration tools (e.g., Docker, Kubernetes) to manage model deployment environments.
• Work with cloud platforms (AWS, GCP, Azure) to deploy and manage AI/ML services.
• Implement security best practices for AI/ML models and data pipelines.
• Troubleshoot and resolve issues related to model deployment and operation.
• Stay updated with the latest MLOps tools, frameworks, and methodologies.
• Document processes, configurations, and procedures to ensure knowledge sharing and continuity.

Requirements:
• Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related field.
• Proven experience (4+ years) in deploying machine learning models in production environments.
• Strong understanding of machine learning, deep learning, NLP, and generative AI techniques.
• Proficiency with MLOps tools and frameworks such as MLflow, Kubeflow, TensorFlow Extended (TFX), or similar.
• Experience with CI/CD tools such as Jenkins, GitLab CI, or CircleCI.
• Proficiency in programming languages such as Python and familiarity with ML/DL frameworks like TensorFlow, PyTorch, and scikit-learn.
• Experience with cloud platforms (AWS, GCP, Azure) and their AI/ML services.
• Knowledge of containerization and orchestration tools (Docker, Kubernetes).
• Strong understanding of version control systems (e.g., Git) and collaborative development workflows.
• Excellent problem-solving skills and the ability to design robust, scalable MLOps solutions.
• Strong communication skills, with the ability to collaborate effectively with cross-functional teams.

Preferred Qualifications:
• Experience with big data technologies and tools such as Hadoop, Spark, and Kafka.
• Familiarity with data visualization tools such as Tableau, Power BI, or similar.

Equal employment opportunity information 


KPMG India has a policy of providing equal opportunity for all applicants and employees regardless of their color, caste, religion, age, sex/gender, national origin, citizenship, sexual orientation, gender identity or expression, disability or other legally protected status. KPMG India values diversity and we request you to submit the details below to support us in our endeavor for diversity. Providing the below information is voluntary and refusal to submit such information will not be prejudicial to you.


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