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Fresher
Not Disclosed
Early Applicant
  • Posted 10 hours ago
  • Be among the first 10 applicants

Job Description

JOB PURPOSE:
Develop and evaluate AI/ML models and prototypes to support research and product innovation. Create, train, and fine-tune AI models using localized and domain-specific data.
Design, implement, and optimize AI applications using modern frameworks and tools. Conduct experiments, analyze results, and document findings for continuous improvement.

KEY RESULT AREAS / RESPONSIBILITIES
Qualifications & Skills Technical Skills
Proficiency in Python programming.
Basic knowledge of machine learning algorithms such as regression, classification, clustering, and neural networks.
Familiarity with AI/ML libraries and frameworks such as:PyTorch
Understanding of data preprocessing, feature engineering, and model evaluation techniques. Basic knowledge of Large Language Models (LLMs) and Generative AI concepts is an advantage.
Familiarity with prompt engineering, Retrieval-Augmented Generation (RAG), or AI agents is a plus. Knowledge of SQL and working with structured datasets.
Exposure to REST APIs and model deployment is a plus. Understanding Linux command line is an advantage.

Preferred Knowledge
Natural Language Processing (NLP) or Computer Vision fundamentals. Understanding of model fine-tuning and transfer learning concepts.
Awareness of AI ethics, responsible AI, and data privacy principles.
Soft Skills
Strong problem-solving and critical thinking abilities.
Curiosity and passion for AI research and emerging technologies.
Ability to work independently as well as in a collaborative team environment. Good documentation and technical writing skills.
Ability to conduct experiments, analyze results, and communicate findings effectively. Time management and willingness to take ownership of assigned tasks.

More Info

Job Type:
Function:
Employment Type:

Key Skills

data preprocessing

Generative AI concepts

model deployment

prompt engineering

Linux command line

Retrieval-Augmented Generation (RAG)

model evaluation techniques

AI agents

feature engineering

Large Language Models (LLMs)

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