AI Engineer:

Key Responsiblities:
System Development: Designing and building AI models, such as neural networks, that learn from data and mimic human cognitive functions
Production Deployment: Transitioning research-level ML models into scalable, operational applications via APIs, microservices, or cloud platforms.
Data Handling & Training: Selecting, managing, and training models using large datasets, including natural language processing (NLP) and computer vision tasks.
Testing & Optimization: Evaluating accuracy, debugging, and improving AI performance to ensure systems run efficiently.
Collaboration: Working with data scientists and software engineers to align AI solutions with business objectives.

Required Skills and Qualifications:
Programming languages: Solid proficiency in Python,



Java, or C++. How to use AI tooling to build up capability. Any UI/API automation framework.
ML Frameworks: Experience with TensorFlow, PyTorch, Keras, or Scikit-learn. How to use MCP server.
Data & Cloud Tools: Proficiency in SQL, Big Data Technologies, and cloud platforms like AWS SageMaker, Azure ML, or Google Cloud
Technical Skills: Expertise in machine learning, deep learning, NLP, computer vision, and algorithm development.
Education: Typically requires a Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field.

📌 Artificial Intelligence Engineer Pune
🏢 CAPCO
📍 Pune