AI/ML Lead

Training Basket; Dadri; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Training Basket is seeking a senior AI/ML leader to design, develop, test, and deploy production-ready AI solutions. You will define technical roadmaps, supervise data prep and model training, and drive scalable pipelines across teams.

You will explore Generative AI, LLMs, and RAG architectures while ensuring privacy, security, and compliant practices. Strong leadership and collaboration are essential.

Qualifications

• Proficient in Python programming.
• Experience with Scikit-learn, TensorFlow, PyTorch.
• Strong background in statistics, probability, algebra, optimization.
• Experience with Pandas, NumPy, and SQL for data processing.
• Knowledge of deep learning, NLP, and computer vision.
• Experience with Generative AI, LLMs, prompts, and RAG.
• Familiarity with LangChain or LlamaIndex.
• Experience deploying models with FastAPI, Flask, or REST APIs.
• Knowledge of MLOps tools, Docker, Kubernetes, CI/CD.
• Cloud familiarity: AWS/Azure/GCP.
• Strong leadership and communication skills.

Responsibilities

• Lead design, development, testing, and deployment of AI/ML models and solutions.
• Define AI/ML strategies and technical roadmaps aligned with business objectives.
• Build and optimize ML/DL models for real-world applications.
• Oversee data preprocessing, feature engineering, model training, validation, and evaluation.
• Work with algorithms for classification, regression, clustering, and predictive analytics.
• Explore Generative AI, LLMs, and RAG solutions.
• Develop scalable AI pipelines and production-ready ML applications.
• Collaborate with data engineers, software developers, product managers, and stakeholders.
• Mentor AI/ML engineers and ensure high-quality technical delivery.
• Monitor model performance, accuracy, scalability, and reliability.
• Ensure data privacy, model security, responsible AI, and compliance.
• Evaluate emerging AI technologies and recommend tools and frameworks.
• Communicate progress, insights, and business impact to stakeholders.

Skills

Python programming

ML theory & practice

Statistics & math

Data analysis (Pandas/NumPy/SQL)

NLP & computer vision

Leadership & communication

Prompt engineering

Tools

TensorFlow

PyTorch

LangChain

LlamaIndex

FastAPI/Flask/REST

Docker

Kubernetes

CI/CD

AWS/Azure/GCP

Job description

Lead the design, development, testing, and deployment of AI/ML models and solutions.

Define AI/ML strategies and technical roadmaps aligned with business objectives.

Build and optimize machine learning and deep learning models for real-world applications.

Oversee data preprocessing, feature engineering, model training, validation, and evaluation.

Work with algorithms for classification, regression, clustering, and predictive analytics.

Explore and implement Generative AI, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG) solutions.

Develop scalable AI pipelines and production-ready ML applications.

Implement MLOps practices for model deployment, monitoring, versioning, and retraining.

Collaborate with data engineers, software developers, product managers, and business stakeholders.

Mentor and guide AI/ML engineers and ensure high-quality technical delivery.

Monitor model performance, accuracy, scalability, and reliability.

Ensure data privacy, model security, responsible AI practices, and compliance.

Evaluate emerging AI technologies and recommend suitable tools and frameworks.

Communicate project progress, technical insights, and business impact to stakeholders.

Requirements

Strong programming skills in Python.

Expertise in machine learning libraries such as Scikit-learn, TensorFlow, and PyTorch.

Strong understanding of statistics, probability, linear algebra, and optimization.

Experience with data processing and analysis using Pandas, NumPy, and SQL.

Knowledge of deep learning, NLP, and computer vision.

Experience with Generative AI, LLMs, prompt engineering, and RAG architectures.

Familiarity with frameworks such as LangChain or LlamaIndex.

Experience with model deployment using FastAPI, Flask, or REST APIs.

Knowledge of MLOps tools, Docker, Kubernetes, and CI/CD pipelines.

Familiarity with cloud platforms such as AWS, Microsoft Azure, or Google Cloud.

Strong leadership, problem-solving, communication, and project management skills.