3562842-Senior Assistant Vice President

EXL; Gurugram District; On-site; INR 1,500,000 - 2,100,000; Full time

Job summary

EXL is seeking a Generative AI and Data Science Engineer with MLOps expertise in Gurgaon, India. This full-time role combines deep data science and ML skills with scalable, production-ready AI solutions across cross-functional teams.

The candidate will design, deploy, and maintain AI/ML systems, ensuring robustness and security in production. Proficiency in Python, ML libraries, and cloud platforms is essential.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field.
• PhD is a plus.

Responsibilities

• Design, develop, and fine-tune generative AI models for NLP, image synthesis, and data augmentation.
• Build, maintain, and optimize CI/CD pipelines for ML models and production deployments.
• Stay current with advancements in generative AI, ML, and MLOps; collaborate on innovative projects.

Skills

Python

TensorFlow

PyTorch

Keras

scikit-learn

Generative AI

Transformers

MLOps

EDA

Data pipelines

Education

Bachelor’s or Master’s in CS/DS/Engineering

PhD (a plus)

Tools

MLflow

Kubeflow

Docker

CI/CD platforms

Job description

Job Description:

Role 1 - Gen AI + DS + ML Ops Job Title: Generative AI and Data Science Engineer with MLOps Expertise Location: Gurgaon, India Employment Type: Full-time Band - D1 / D2 About the Role: We are seeking a versatile and highly skilled Generative AI and Data Science Engineer with strong MLOps expertise. This role combines deep technical knowledge in data science and machine learning with a focus on designing and deploying scalable, production-level AI solutions. You will work with cross-functional teams to drive AI/ML projects from research and prototyping through to deployment and maintenance, ensuring model robustness, scalability, and efficiency.

Responsibilities:

• Generative AI Development and Data Science: Design, develop, and fine-tune generative AI models for various applications such as natural language processing, image synthesis, and data augmentation. Perform exploratory data analysis (EDA) and statistical modeling to identify trends, patterns, and actionable insights. Collaborate with data engineering and product teams to create data pipelines for model training, testing, and deployment. Apply data science techniques to optimize model performance and address real-world business challenges.
• Machine Learning Operations (MLOps): Implement MLOps best practices for managing and automating the end-to-end machine learning lifecycle, including model versioning, monitoring, and retraining. Build, maintain, and optimize CI/CD pipelines for ML models to streamline development and deployment processes. Ensure scalability, robustness, and security of AI/ML systems in production environments. Develop tools and frameworks for monitoring model performance and detecting anomalies post-deployment.
• Research and Innovation: Stay current with advancements in generative AI, machine learning, and MLOps technologies and frameworks. Identify new methodologies, tools, and technologies that could enhance our AI and data science capabilities. Engage in R&D initiatives and collaborate with team members on innovative projects.

Requirements:

• Educational Background: Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related field. PhD is a plus.
• Technical Skills: Proficiency in Python and familiarity with machine learning libraries (e.g., TensorFlow, PyTorch, Keras, scikit-learn). Strong understanding of generative AI models (e.g., GANs, VAEs, transformers) and deep learning techniques. Experience with MLOps frameworks and tools such as MLflow, Kubeflow, Docker, and CI/CD platforms. Knowledge of data science techniques for EDA, feature engineering, statistical modeling, and model evaluation. Familiarity with cloud platforms (e.g., AWS, Google Cloud, Azure) for deploying and scaling AI/ML models.
• Soft Skills: Ability to collaborate effectively across teams and communicate complex technical concepts to non-technical stakeholders. Strong problem-solving skills and the ability to innovate in a fast-paced environment.
• Preferred Qualifications: Prior experience in designing and deploying large-scale generative AI models. Proficiency in SQL and data visualization tools (e.g., Tableau, Power BI). Experience with model interpretability and explainability frameworks.