AI/ML/GEN AI Engineer

Infosys; Bengaluru; On-site; INR 1,200,000 - 2,100,000; Full time

Job summary

Infosys is seeking a dynamic data science lead with deep expertise in Python, ML, NLP GenAI, and end-to-end model lifecycle. The candidate should guide development teams on ML use case implementation and drive GenAI solutions, including RAG and Agentic AI, leveraging cloud AI services across Azure, AWS, and GCP.

Hands-on experience in putting AI models into production and ensuring Responsible AI practices is highly valued.

Qualifications

• Bachelor-level computing degree required.
• Hands-on Python-based ML pipeline experience.
• Experience with NLP GenAI techniques and productionisation.
• Experience building AI solutions for enterprise apps and coordinating teams.

Responsibilities

• Collect, profile, and preprocess data for ML experiments.
• Apply supervised, unsupervised, and reinforcement learning techniques.
• Design, develop, and deploy ML models using Python and frameworks.
• Implement NLP solutions including tokenization, vectorization, and semantic analysis.
• Develop GenAI solutions like RAG systems and Agentic AI.
• Monitor production models and plan retraining strategies.
• Ensure Responsible AI across ML workflows.
• Present insights to stakeholders and plan new use cases.
• Collaborate with data scientists and engineers on training/evaluation/deployment.
• Utilize Azure/AWS/GCP AI services.

Skills

Python

ML lifecycle

NLP GenAI

MLOps

Copilot Studio

Responsible AI

Prompt engineering

Explainable AI

Education

Bachelor of Computer Applications

Bachelor of Computer Science

Bachelor of Engineering

Bachelor of Technology

Tools

TensorFlow

PyTorch

Scikit-learn

Flask

Django

Azure

AWS

GCP

Kubernetes

Docker

Kafka

Job description

Job Summary

We are seeking a dynamic candidate with expertise in Python, Machine Learning, Natural Language Processing (NLP) GenAI techniques. The ideal candidate should have hands‑on experience in designing and implementing end‑to‑end data science and ML solutions, including model productionisation and guiding development teams on ML use case implementation. A strong background in AI/ML solutioning combined with experience in NLP GenAI solutions is highly preferred. Candidates with experience in Microsoft Copilot Studio will be a great asset to the team.

Responsibilities

• Perform data collection, profiling, exploration data analysis (EDA), and data preparation.
• Apply a range of ML techniques including supervised, unsupervised, and reinforcement learning.
• Design, develop, and deploy machine learning models using Python and popular ML frameworks
• Implement NLP solutions using NLP techniques like preprocessing, tokenization, vectorization, and semantic analysis.
• Develop and deploy GenAI solutions such as RAG systems and Agentic AI.
• Monitor model performance in production and implement retraining strategies.
• Adhere to and implement Responsible AI principles in all ML workflows.
• Present analytical insights to business stakeholders and project teams.
• Propose ML-based solutions and provide effort estimates for new use cases.
• Collaborate with data scientists and engineers on model training, evaluation, and deployment.
• Utilize AI services from cloud platforms such as Azure, AWS, and GCP.

Technical Requirements

• Strong proficiency in Python for data processing, automation, and model development.
• Deep understanding of ML model lifecycle: training, evaluation, and deployment.
• Strong proficiency in Python and ML frameworks (e.g., TensorFlow, PyTorch, Scikit‑learn).
• Good to have experience integrating GenAI capabilities into enterprise applications using platforms like Microsoft Copilot Studio.
• Good to have experience in monitoring model performance and conduct thorough evaluations using metrics such as Precision, Recall, F1 Score, and BLEU
• Understanding of Responsible AI practices including model fairness, transparency, and auditability.
• Hands‑on experience with Python‑based web applications for AI/ML use cases.
• Solid knowledge of cloud‑based AI services (Azure, AWS, GCP).

Additional Responsibility

• Experience with MLOps frameworks for model lifecycle, versioning, deployment, and monitoring - such as Azure Machine Learning or AWS Sagemaker.
• Experience with Python‑based web frameworks such as Flask and Django is essential, and familiarity with front‑end technologies like Angular or React.js is a valuable addition.
• Hands‑on experience in fine‑tuning large language models (LLM) using techniques such as LoRA and QLoRA is highly valued.
• Experience with Kubernetes, docker containerization, and Kafka is preferred. Knowledge on model optimization, model distillation, quantization is an advantage.

Educational Requirement

• Bachelor of Computer Applications
• Bachelor of Computer Science
• Bachelor of Engineering
• Bachelor of Technology

Preferred Skills

• AI Engineering
• AI/ML Solution Architecture and Design
• Generative AI
• Conversational AI Platform
• Prompt Engineering
• Responsible AI
• Explainable AI

Service Line

Engineering Services