Python AI ML Developer

2 weeks ago

Chennai, Tamil Nadu, India Virtusa Full time
Python AI ML Developer - CREQ190778 Description

Job Description:
Expertise in ETL tools, technologies, and processes.
Expertise in Big Data Tools and databases
Programming languages Python, Java FSD and Scala
Strong experience of machine learning concepts, including algorithms, and statistics.
Knowledge of common machine learning techniques, such as Naive Bayes classifiers, conditional probability.
Developing solution using Large Language models for generating new content, Summarization, Classification and Open-Domain Q+A use cases.
Candidate is expected to have minimum 5 years of experience on the below areas
Building data pipeline to extract information from unstructured documents using NLP , LLM and Computer Vision. Good knowledge in LLM fine tuning techniques and building RAG architecture pattern.
Developing probabilistic and predictive AI models for data classification and retrieval problems.
Buildings tools for evaluating the performance of the models and engage retraining if required.
Using open source pre-training models for classification/ computer vision / NLP tasks.

Large Language Models (LLM): Experience with developing solutions using large language models for generating new content, summarization, classification, and open-domain Q+A use cases.

Natural Language Processing (NLP): Proficiency in building data pipelines to extract information from unstructured documents using NLP and LLM.

Computer Vision:
Knowledge of computer vision techniques to process and analyze images or videos.

LLM Fine-Tuning Techniques:
Good understanding of fine-tuning techniques for large language models.

RAG Architecture Pattern:
Experience with building systems using the Retrieval-Augmented Generation (RAG) architecture pattern.

Probabilistic and Predictive AI Models:
Ability to develop probabilistic and predictive AI models for data classification and retrieval problems.

Model Evaluation and Retraining:
Skills in building tools for evaluating the performance of the models and engaging retraining if required.
Pre-training Models: Experience with using open-source pre-training models for classification, computer vision, and NLP tasks.
Primary Skill.
LLM Fine-Tuning
Prompt Engineering
Python
Secondary skill.
MangoDB
Primary Location Chennai, Tamil Nadu, India Job Type Experienced Primary Skills Python Years of Experience 5 Qualification

Job Description:
Expertise in ETL tools, technologies, and processes.
Expertise in Big Data Tools and databases
Programming languages Python, Java FSD and Scala
Strong experience of machine learning concepts, including algorithms, and statistics.
Knowledge of common machine learning techniques, such as Naive Bayes classifiers, conditional probability.
Developing solution using Large Language models for generating new content, Summarization, Classification and Open-Domain Q+A use cases.
Candidate is expected to have minimum 5 years of experience on the below areas
Building data pipeline to extract information from unstructured documents using NLP , LLM and Computer Vision. Good knowledge in LLM fine tuning techniques and building RAG architecture pattern.
Developing probabilistic and predictive AI models for data classification and retrieval problems.
Buildings tools for evaluating the performance of the models and engage retraining if required.
Using open source pre-training models for classification/ computer vision / NLP tasks.

Large Language Models (LLM): Experience with developing solutions using large language models for generating new content, summarization, classification, and open-domain Q+A use cases.

Natural Language Processing (NLP): Proficiency in building data pipelines to extract information from unstructured documents using NLP and LLM.

Computer Vision:
Knowledge of computer vision techniques to process and analyze images or videos.

LLM Fine-Tuning Techniques:
Good understanding of fine-tuning techniques for large language models.

RAG Architecture Pattern:
Experience with building systems using the Retrieval-Augmented Generation (RAG) architecture pattern.

Probabilistic and Predictive AI Models:
Ability to develop probabilistic and predictive AI models for data classification and retrieval problems.

Model Evaluation and Retraining:
Skills in building tools for evaluating the performance of the models and engaging retraining if required.
Pre-training Models: Experience with using open-source pre-training models for classification, computer vision, and NLP tasks.
Primary Skill.
LLM Fine-Tuning
Prompt Engineering
Python
Secondary skill.
MangoDB
Travel No

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