AI Research Scientist

Training Basket; Dadri; On-site; INR 600,000 - 1,000,000; Full time

Job summary

Training Basket seeks an AI/ML researcher to design and implement models across NLP, CV, and generative AI domains. You will prototype solutions, run experiments, and publish findings to inform product development.

You will collaborate with engineering and data science teams, analyze datasets, and evaluate models using robust metrics, while staying current with the latest AI research trends.

Qualifications

• Strong programming skills in Python.
• Good understanding of ML and DL concepts.
• Knowledge of mathematics, probability, statistics, linear algebra, and optimization.
• Experience with frameworks such as PyTorch or TensorFlow.
• Understanding of algorithms, model training, validation, and evaluation techniques.
• Knowledge of NLP, Computer Vision, or Generative AI is an advantage.
• Familiarity with data processing libraries such as NumPy, Pandas, and Scikit-learn.
• Strong analytical, research, and problem-solving abilities.
• Excellent technical documentation and communication skills.

Responsibilities

• Research, design, and develop AI/ML models and algorithms.
• Explore Deep Learning, NLP, and Computer Vision techniques.
• Conduct experiments, evaluate model performance, and optimize algorithms.
• Analyze large datasets to identify patterns, trends, and insights.
• Develop prototypes and proof-of-concept solutions for AI-based applications.
• Collaborate with engineering and data science teams to translate research findings into practical applications.
• Evaluate models using appropriate performance metrics and statistical methods.
• Document research findings, experiments, methodologies, and results.

Skills

Python programming

ML concepts

Deep Learning concepts

Maths / statistics / linear algebra

NLP / CV knowledge

Analytical / research / problem‑solvng

Documentation / communication

Tools

PyTorch

TensorFlow

NumPy

Pandas

Scikit-learn

Job description

Research, design, and develop AI and Machine Learning models and algorithms.

Explore advanced techniques in Deep Learning, Natural Language Processing (NLP), and Computer Vision.

Conduct experiments, evaluate model performance, and optimize algorithms.

Analyze large datasets to identify patterns, trends, and meaningful insights.

Develop prototypes and proof-of-concept solutions for AI-based applications.

Implement and test machine learning algorithms using Python and relevant frameworks.

Read and analyze research papers to explore emerging AI techniques and methodologies.

Collaborate with engineering and data science teams to translate research findings into practical applications.

Evaluate models using appropriate performance metrics and statistical methods.

Document research findings, experiments, methodologies, and results.

Stay updated with the latest advancements in Generative AI, Large Language Models (LLMs), and AI research.

Requirements

Strong programming skills in Python.

Good understanding of Machine Learning and Deep Learning concepts.

Knowledge of mathematics, probability, statistics, linear algebra, and optimization.

Experience with frameworks such as PyTorch or TensorFlow.

Understanding of algorithms, model training, validation, and evaluation techniques.

Knowledge of NLP, Computer Vision, or Generative AI is an advantage.

Familiarity with data processing libraries such as NumPy, Pandas, and Scikit-learn.

Strong analytical, research, and problem-solving abilities.

Excellent technical documentation and communication skills.