AI Engineer – Roles & Responsibilities

1. Design & Develop AI Models

Build, train, and optimize machine learning (ML) and deep learning models

Work with algorithms such as regression, classification, clustering, NLP, and computer vision

Select appropriate model architectures based on business use cases

2. Data Handling & Preprocessing

Collect, clean, and preprocess structured and unstructured data

Perform feature engineering and data transformation

Ensure data quality, consistency, and scalability

3. Model Training & Evaluation

Train models using frameworks like TensorFlow, PyTorch, or Scikit-learn

Evaluate model performance using metrics (accuracy, precision, recall, F1-score)

Perform hyperparameter tuning and model optimization

4. Deployment & Integration

Deploy AI models into production environments (APIs, microservices, cloud)

Integrate AI solutions into web or mobile applications

Work with cloud platforms like AWS, Google Cloud, or Microsoft Azure

5. Automation & AI Pipelines

Build end-to-end ML pipelines (data ingestion → training → deployment)

Automate workflows using CI/CD for ML (MLOps practices)

Monitor model performance and retrain when needed

6. AI Research & Innovation

Stay updated with latest AI trends, research papers, and tools

Experiment with new models (LLMs, generative AI, reinforcement learning)

Apply cutting-edge techniques to solve real-world problems

7. Performance Optimization





Optimize models for speed, scalability, and cost efficiency

Use techniques like model pruning, quantization, and distributed training

8. Collaboration & Communication

Work with data scientists, software engineers, and product teams

Translate business problems into AI solutions

Document models, workflows, and technical decisions

9. Ethics & Responsible AI

Ensure fairness, transparency, and bias mitigation in AI systems

Follow data privacy and security standards

Common Tools & Technologies

Programming: Python, R

Libraries: TensorFlow, PyTorch, Scikit-learn

NLP: Transformers, Hugging Face

Databases: SQL, NoSQL

DevOps/MLOps: Docker, Kubernetes, CI/CD tools

Version Control: Git

Optional Specializations

NLP Engineer (chatbots, LLMs)

Computer Vision Engineer

Generative AI Engineer

AI for Cybersecurity / Policing (relevant to your interest

Job Types: Full-time, Fresher, Internship

Pay: From ₹400,000.00 per year

Advantages:

- Cell phone reimbursement
- Commuter assistance
- Adaptable schedule
- Food provided
- Health insurance
- Internet reimbursement
- Leave encashment
- Life insurance
- Paid sick time
- Paid time off
- Provident Fund
- Work from home

Experience:

- total work: 1 year (Preferred)

Location:

- Baner, Pune, Maharashtra (Required)

Work Location: Hybrid remote in Baner, Pune, Maharashtra

📌 AI Engineer Intern (India)
🏢 Impulsemacro Innovation Private
📍 India