Internship – AI/ML Engineering

Job Description

Duration: 3–4 Months
Location: Bengaluru / Remote
Mode: Full-Time Internship

About the Role

This internship is designed for candidates who want to bridge the gap between machine learning theory and real-world product deployment. You’ll work on model development, data preprocessing, inference APIs, and integrating AI components into production workflows.

Key Responsibilities

• Develop, train, and evaluate ML models using frameworks like PyTorch or TensorFlow.
• Build and optimize preprocessing, feature engineering, and model pipelines.
• Work with REST APIs and backend services to serve models in production.
• Analyze datasets to extract insights, evaluate accuracy, and improve performance.
• Support model monitoring, versioning, and inference optimization.

Required Skills

• Strong understanding of Python and ML fundamentals.
• Experience with ML libraries such as Scikit-learn, PyTorch, or TensorFlow.
• Familiarity with data structures, statistics, and algorithms.
• Knowledge of Git and basic Linux workflows.

Nice to Have (Bonus)

• Exposure to FastAPI, Docker, or Kubernetes for model deployment.
• Familiarity with NLP, computer vision, or LLM fine-tuning.
• Understanding of vector databases or embeddings.

Who Should Apply

• Students passionate about taking ML beyond notebooks and into production.
• Candidates with hands-on projects, Kaggle experience, or research exposure.
• Individuals eager to learn, experiment, and solve real product challenges.

What You’ll Gain

• Practical experience shipping AI/ML features in a real product environment.
• Learn end-to-end model lifecycle: data → model → API → deploy → monitor.
• Exposure to MLOps concepts.
• Internship certificate on successful completion.