Artificial Intelligence (AI) Internship in Pune at Assetcues Solutions
Artificial Intelligence (AI)
Assetcues Solutions Private LimitedLocation(s): Pune
DESCRIPTION
About the internship
Selected intern's day-to-day responsibilities include:
1. Implementing and testing AI models to solve specific business problems or enhance product features.
2. Training, evaluating, and fine-tuning machine learning models for tasks such as NLP or Computer Vision.
3. Utilizing LLMs and generative AI tools to develop prototypes, assist in coding, and automate workflows.
4. Partnering with engineering teams to integrate AI models into software architectures and identify practical improvements.
5. Documenting model architectures, experiments, and technical findings for internal teams and stakeholders.
6. Staying updated with the latest advancements in AI/ML to suggest innovative approaches for ongoing projects.
Skill(s) required
Who can apply
Only those candidates can apply who:
1. are available for full time (in-office) internship
2. can start the internship between 31st Mar'26 and 5th May'26
3. are available for duration of 4 months
4. are from Pune only
5. have relevant skills and interests
Other requirements
1. Currently pursuing or recently completed a degree in Computer Science, Artificial
Intelligence, Data Science, or a related technical field.
2. Solid understanding of the Machine Learning lifecycle, data structures, and fundamental algorithms.
3. Strong proficiency in Python, including libraries like NumPy, Pandas, and Scikit-learn.
4. Comfortable using AI-driven development tools for assistance, with the judgment to verify results carefully.
5. High attention to detail, creative problem-solving ability, and a proactive, eager-to-learn mindset.
6. Experience with deep learning frameworks like PyTorch or TensorFlow.
7. A portfolio of projects related to ML, NLP, or AI-integrated applications.
8. Familiarity with using APIs to connect AI models to external services.
9. Hands-on experience with FastAPI or Flask for building and deploying AI-related web services.
10. Familiarity with LLM orchestration frameworks like LangChain or LangGraph for building agentic workflows.
11. Understanding of database management and interacting with databases to store or retrieve model-related data.
12. Basic knowledge of cloud platforms such as AWS, Azure, or GCP for deploying and managing AI solutions.