Job DescriptionWe 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 excellent asset to the team.
Roles 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 Requirement




- 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).

- Hands-on experience with Natural Language Processing (NLP) techniques and tools.

- Experience in developing Generative AI solutions, including:

- Retrieval-Augmented Generation (RAG) pipelines for enhanced contextual responses.

- Agent-based AI systems leveraging Large Language Models (LLMs) for autonomous task execution and decision-making

- 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).
Educational RequirementMaster Of Engineering,Master Of Technology,MCA,MSc,Bachelor of Engineering,Bachelor Of Technology,BCA,BSc
Preferred SkillsTechnology->AI-AI Engineering->AI/ML Solution Architecture and Design->generative ai,Technology->AI-Generative AI->Generative AI - Basic,Technology->AI-Generative AI->Prompt Engineering,Technology->OpenSystem->Python - OpenSystem->Python
Service LineEngineering Services

📌 GEN AI Engineer (Bengaluru)
🏢 Infosys
📍 Bengaluru