Senior Machine Learning Engineer

Infosys; Hyderabad; On-site; INR 1,800,000 - 3,200,000; Full time

Job summary

Infosys in Hyderabad seeks an experienced NLP/GenAI specialist to design and deploy ML, NLP solutions for enterprise applications. You will build text classification, information extraction, sentiment analysis, NER, and summarization models, and develop GenAI workflows.

You will fine-tune transformer models, implement RAG pipelines, and create AI copilots and chatbots. Mentoring junior engineers and collaborating with stakeholders are expected.

Qualifications

• Bachelor's or higher in engineering or related field.
• Experience in NLP/ML for enterprise applications.
• Hands-on with transformer models and GenAI.
• Experience in production ML pipelines (MLOps).

Responsibilities

• Design, develop, and deploy ML and NLP solutions for business-critical apps.
• Build and optimize text classification, extraction, sentiment analysis, NER, summarization.
• Develop and fine-tune Transformer-based models and LLM-powered apps.
• Evaluate model performance and improve accuracy and efficiency.
• Design Retrieval-Augmented Generation pipelines.
• Create AI copilots, chatbots, and intelligent search solutions.
• Apply prompt engineering to optimize outputs.
• Develop agentic AI workflows with orchestration frameworks.
• Mentor junior ML engineers and participate in reviews.

Skills

NLP Development

Text classification

Information extraction

Sentiment analysis

Entity recognition

Summarization

Transformer models

GenAI applications

Education

Bachelor of Engineering

BCS

BBA

BCom

MCA

MSc

Tools

MLflow

Job description

Educational Requirements

• Bachelor of Engineering
• BCS
• BBA
• BCom
• MCA
• MSc

Service Line

• Data Analytics Unit

Responsibilities

• Machine Learning NLP Development
• Design, develop, and deploy Machine Learning and NLP solutions for business-critical applications.
• Build and optimize text classification, information extraction, sentiment analysis, entity recognition, summarization, and conversational AI systems.
• Develop and fine-tune Transformer-based models and LLM-powered applications.
• Evaluate model performance and implement improvements for accuracy, scalability, and efficiency.
• Generative AI LLM Applications
• Develop GenAI applications using Large Language Models (LLMs).
• Design and implement Retrieval-Augmented Generation (RAG) pipelines.
• Build AI copilots, chatbots, virtual assistants, and intelligent search solutions.
• Apply prompt engineering techniques to optimize model outputs.
• Develop agentic AI workflows using modern AI orchestration frameworks.

Additional Responsibilities

• Research Innovation
• Stay updated with advancements in NLP, Generative AI, LLMs, and Machine Learning.
• Evaluate emerging AI technologies and recommend adoption where appropriate.
• Conduct experiments and proof-of-concepts (POCs) to solve complex business problems.
• Leadership Mentoring
• Mentor junior ML engineers and data scientists.
• Conduct code reviews, model reviews, and design reviews.
• Promote best practices in machine learning engineering and AI development.
• Collaborate with business stakeholders, product teams, and engineering leaders.

Technical and Professional Requirements

• Data Preparation
• Process and analyze large-scale structured and unstructured datasets.
• Feature Engineering
• Perform text preprocessing, tokenization, feature extraction, and embedding generation.
• Model Deployment MLOps
• Deploy, monitor, and maintain ML models in production environments.
• MLflow
• Implement model versioning, tracking, and serving using MLflow.
• Develop CI/CD pipelines for machine learning workflows.
• Monitor model drift, performance metrics, and system reliability.

Preferred Skills

• AI-Traditional AI: Microsoft LUIS, NLP
• AI-Data science: Machine Learning
• AI-Generative AI: Generative AI - Basic