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Job Closed

AI Engineer Intern

  • Source: Indeed
  • Shyena Tech Yarns Pvt Ltd
  • On-site
  • State of Mahārāshtra, India
  • Full-Time
  • Junior

Job Description

Job Type: Internship / Entry-Level (Full-Time Opportunity Post Internship)

Contract Terms: This is 30 months contract.

Company Overview

Shyena Tech Yarns is a technology-driven organization focused on building intelligent, scalable, and data-powered solutions. We leverage Artificial Intelligence, Machine Learning, and Advanced Analytics to solve real-world business problems. At Shyena Tech Yarns, we provide a strong learning environment for fresh graduates to work on cutting-edge AI technologies, including LLMs, NLP, and Deep Learning, under the guidance of experienced

Job Summary

We are looking for passionate AI Developers / Data Scientist with strong fundamentals in Machine Learning, Deep Learning, NLP, and Large Language Models (LLMs). The candidate will work on developing and testing AI applications. This role is ideal for candidates eager to start a career in applied AI and data-driven systems.

Roles & Responsibilities

  • Develop, train, and evaluate Machine Learning and Deep Learning models
  • Work on NLP tasks such as text classification, sentiment analysis, NER, and summarization
  • Assist in developing and fine-tuning Large Language Models (LLMs)
  • Perform data pre-processing, feature engineering, and exploratory data analysis
  • Implement ML/DL pipelines using Python
  • Integrate AI models into applications via APIs
  • Experiment with model optimization, tuning, and performance improvement
  • Document experiments, models, and workflows
  • Collaborate with cross-functional teams including backend and product teams

Key Skills

  • Python
  • Machine Learning
  • Deep Learning
  • Natural Language Processing (NLP)
  • Large Language Models (LLMs)
  • Keras /TensorFlow / PyTorch
  • Scikit-learn
  • Pandas, NumPy
  • REST APIs (basic)
  • Docker

Required Candidate Profile

  • Fresher or candidate with 0–6 months experience
  • Strong understanding of ML algorithms (Regression, Classification, Clustering)
  • Good knowledge of Deep Learning concepts (CNN, RNN, Transformers – basics)
  • Understanding of NLP fundamentals and text processing techniques
  • Familiarity with LLM concepts and prompt engineering
  • Strong programming skills in Python
  • Ability to work with structured and unstructured data
  • Good analytical, problem-solving, and communication skills
  • Willingness to learn and adapt to new AI technologies

Preferred Skills (Good to Have)

  • Experience with Hugging Face Transformers
  • Exposure to model deployment (FastAPI / Flask)
  • Basic understanding of vector databases (FAISS, Pinecone, etc.)
  • Knowledge of cloud platforms (AWS / GCP / Azure – basics), deployment basics
  • AI/ML projects, internships, or research experience

Perks & Benefits

  • Hands-on experience with real-world AI projects
  • Mentorship from AI and data science experts
  • Opportunity to work on LLMs and GenAI use cases
  • Learning and career growth opportunities
  • Collaborative and innovation-driven work culture

Required Qualifications & Skills

  • Bachelor’s, Master’s in Computer Science, Electrical Engineering, Artificial Intelligence, or equivalent experience.
  • Strong Python programming skills and fundamentals of software design and optimization.
  • In-depth knowledge of ML/DL techniques and algorithms, with hands-on exposure to CNNs, RNNs (LSTM), Transformers (BERT, BART, GPT/T5, Megatron, LLMs).

Academic Eligibility

  • Excellent academic record throughout.
  • Minimum 90% or above in 10th standard.
  • Minimum 85% or above in 12th standard and Graduation.
  • Only 2025 or 2026 pass-out candidates are eligible to apply.

Pay: ₹8,000.00 - ₹10,000.00 per month

Work Location: In person

Skills

  • Python
  • processing-js
  • Keras
  • Tensorflow
  • PyTorch
  • Scikit-learn
  • Pandas
  • NumPy
  • Docker
  • Transformers
  • hugging-face
  • FastAPI
  • Flask
  • FAISS
  • amazon-web-services
  • google-cloud-platform
  • microsoft-azure
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