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 current 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 Responsibilities

- 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

- Master of Comp. Applications
- Master of Engineering
- Master of Science
- Master of Technology
- Bachelor of Comp. Applications
- Bachelor of Science
- Bachelor of Engineering
- Bachelor of Technology

Preferred Skills

- Technology->AI-AI Engineering->AI/ML Solution Architecture and Design
- Technology->AI-Generative AI->Generative AI - Basic

Service Line

Engineering Services

📌 AI/ML/GEN AI Engineer (Bengaluru)
🏢 Infosys
📍 Bengaluru