AI / Machine Learning Engineer Intern

Technix-Technology Solutions Private Limited; Patna; On-site; INR 167,400 - 279,000; Full time

Benefits offered by this job

Mentorship from senior AI engineers

Certificate of Completion

Opportunity for full-time ML Engineer role

Job summary

Technix-Technology Solutions Private Limited in Patna is seeking a passionate AI / ML Intern to work on real-world machine learning applications. The role involves collaborating with teams to design, train, and deploy ML models.

The ideal candidate should have hands-on experience with ML models and be available for a full-time, 6-month internship. Exposure to NLP or Computer Vision is a plus. A stipend begins after three months, and there are opportunities for mentorship from senior engineers.

Qualifications

• Hands-on experience with building and training ML models.
• Strong understanding of regression, classification, and clustering.
• Must be available full-time for a 6-month internship.

Responsibilities

• Collect, clean, and preprocess datasets.
• Experiment with different ML models and optimize accuracy.
• Document research findings and experiments.

Skills

Python

Machine Learning Algorithms

NumPy

Pandas

TensorFlow or PyTorch

Problem Solving

Documentation

Education

Bachelor’s / Master’s degree in Computer Science or Data Science

Tools

Jupyter Notebook

AWS

GCP

Azure

Docker

Job description

Skills Required: Python, NumPy, Pandas, Scikit-Learn, TensorFlow or PyTorch, Machine Learning Algorithms, Data Preprocessing, Model Evaluation, Feature Engineering, Deep Learning Basics, Problem Solving, Documentation & Communication

Educational Qualification: Bachelor’s / Master’s degree in Computer Science, Data Science, AI / ML, Mathematics, Statistics, or related branches.

Internship Type: DEFERRED STIPEND

Stipend Policy: Starts after 3rd month

Workplace Options: Work From Office

Opening Summary

We are looking for a passionate and research-driven AI / ML Intern who is excited to work on real-world applications of machine learning. You will collaborate with engineering and product teams to design, train, evaluate, and deploy machine learning models that solve meaningful business problems.

Requirements

• Hands-on experience with building and training ML models (academic or personal projects acceptable).
• Strong understanding of ML concepts such as regression, classification, clustering, and evaluation metrics.
• Ability to work with Python-based ML tools and libraries.
• Experience using Jupyter Notebook or similar environments for experimentation.
• Must be available full-time for the entire 6-month internship period.
• Must submit at least one ML project or GitHub repository as proof of work.

Responsibilities

• Collect, clean, and preprocess structured and unstructured datasets.
• Experiment with different ML models, evaluate performance, and optimize accuracy and latency.
• Build and test ML pipelines including feature extraction, model training, and inference.
• Implement algorithms for supervised, unsupervised, or deep learning based on project needs.
• Document research findings, experiments, and architecture decisions.
• Work with developers to integrate ML models into applications using APIs.
• Stay updated with AI trends, new research, and model improvement techniques.

Preferred Qualification

Exposure to NLP, Computer Vision, or LLM-based applications. Familiarity with cloud platforms (AWS, GCP, Azure) for model deployment. Experience with MLOps concepts such as model lifecycle, pipelines, or Docker. Basic understanding of SQL or NoSQL databases for data storage and retrieval. Coursework or certifications in AI / ML from leading platforms.

• Hands-on experience solving real AI / ML problems
• Mentorship from senior AI engineers and data scientists
• Certificate of Completion
• Opportunity to convert into a full-time ML Engineer role based on performance

Stipend Eligibility Criteria

• Complete the full 6-month internship without discontinuation.
• Maintain minimum 80% attendance (as per organizational policy).
• Meet assigned deliverables such as model experimentation, documentation, and integration.
• Participate actively in sprint ceremonies, reviews, and team discussions.
• Comply with organizational ethics, confidentiality, and performance expectation
• Early exit or termination due to performance/disciplinary reasons will void stipend eligibility.