AI ML Engineer

Job Description:

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

Key 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 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

Preferred Skills:

Technology->AI-Generative AI->Prompt Engineering,Technology->AI-Responsible AI->Responsible AI->explainable ai,Technology->AI-AI Engineering->AI/ML Solution Architecture and Design->generative ai,Technology->AI-Generative AI->Conversational AI Platform