Kreeda Labs
Website:
kreedalabs.com
Job details:
Job description
Job Role- AI/ML Engineer Intern
Job Type: Full-Time Internship
Mode: WFO - Onsite
Location: Pune
Notice Period: Immediate to 15 days
Experience: 0 - 6 months
Most AI internships end in a notebook. This one is expected to end in production.
Plenty of companies will let you train a model on a clean dataset and present the accuracy score at the end of six months. We would rather hand you a messy real-world problem, a client with an actual deadline, and a senior engineer who will tell you honestly when your approach will not hold up.
If you want to find out what happens to a model after the training run finishes, this is the right place to spend six months.
About Kreeda Labs
We are an AI and full stack product engineering company based in Pune. We have delivered 75+ production systems for 40+ clients across three continents, spanning fashion, HR tech, healthcare, insurance, eLearning and supply chain.
Our work includes engagements with Ralph Lauren, Tata Group / Tata Play, Patanjali and Multiversity. AI is not a side experiment here. It is what a growing share of our client work is built on.
What You'll Do
You will work alongside our AI engineering team on live client problems, starting with well-scoped pieces and taking on more as you prove you can carry them.
Build
• Build, train and evaluate machine learning models for real use cases, not curated datasets
• Handle the unglamorous half of the work properly: data collection, cleaning, transformation and analysis
• Experiment with training approaches and optimisation, and be able to explain why one worked
Explore
• Prototype GenAI applications, including RAG pipelines and vector database integrations
• Work with LangChain, LangGraph or similar frameworks as you build agentic and retrieval-based workflows
• Read papers and open-source projects and turn the promising ones into working proofs of concept
Ship
• Contribute to the backend components and APIs that carry a model into an application
• Get exposure to how models are deployed, monitored and kept working on AWS, Azure or GCP
• Document what you built, what you tried, and what the results actually mean
Who Can Apply
Must have
• Final-year student or recent graduate in Computer Science, Data Science, AI/ML or a related field
• Solid Python, with working knowledge of scikit-learn and either TensorFlow or PyTorch
• Familiarity with common ML algorithms and data preprocessing techniques
• Exposure to SQL and general data handling
• At least one project, academic or personal, that you can walk us through and defend
• Strong problem-solving instinct and clear communication
Good to have
• Exposure to GenAI concepts: LangChain, LangGraph, CrewAI, AutoGen, RAG or vector databases
• Hands-on NLP or Computer Vision work
• Familiarity with FastAPI or Django
• Awareness of MLOps practices and model deployment
• A real understanding of the mathematics underneath the algorithms
You are not expected to have all of this. What we look for is depth in something rather than a passing familiarity with everything.
What Makes This Different
The gap between a model that scores well and a system a client will pay for is where most AI work actually happens, and it is the part academic projects rarely reach. Here you will see it directly: latency that matters, outputs that need to be reliable rather than merely impressive, costs that scale with usage, and users who will find the edge case you did not think of.
You will also work in an engineering environment where AI-assisted development is normal. We expect you to use those tools well and still be able to review and defend everything that ends up in the repository.
What You'll Gain
• Hands-on project experience with mentorship from engineers who ship AI systems for a living
• Exposure to GenAI, RAG and agentic architectures on real client work
• Practical experience with cloud platforms and production-grade environments
• A Pre-Placement Offer for interns who perform
This Role May Not Be for You If
You want to stay on the research side and avoid engineering, you are uncomfortable working on data cleaning and pipelines as well as modelling, or you are looking for a certificate at the end of six months rather than a body of work.
How to Apply
Apply through LinkedIn, or send your CV along with your GitHub, Kaggle or project links to [careers@kreedalabs.com] with the subject line AI/ML Engineer Intern, Pune.
Tell us in two lines about a model or project of yours that did not work, and what you learned from it. That will get our attention faster than a list of courses.
See what you would be building at www.kreedalabs.com
Click on Apply to know more.
