This is a hands-on, project-driven internship where you will work directly alongside our ML/AI Engineers and AI Agent Engineers. You will contribute to real deliverables, not just observe, spanning computer vision, multimodal learning, agentic systems, and RAG pipelines.The track you work on is flexible and will be matched to your interests, background, and the team's current priorities. We believe great interns come from many different starting points, curiosity, logical thinking, and a willingness to learn matter more than a perfect resume.By the end of 6 months, you will have worked on production-adjacent AI systems and built a portfolio of meaningful, demonstrable work
Basic Technical Skills (Good to Have, Not All Required)
• Python basics — ability to write scripts, run notebooks, and understand existing code.
• Familiarity with any ML/DL concept — even from coursework or self-study counts.
• Exposure to tools like Jupyter, Google Colab, HuggingFace, or OpenAI API.
• Basic understanding of NLP, computer vision, or LLMs — at any depth.
• Comfortable using Git for version control.
What You Will Work On
Depending on your track, your day-to-day work may include contributions across any of the following areas:
Vision Track
• Assist with dataset collection, labeling, and augmentation
• Run and evaluate pre-trained models (YOLO, ResNet, SAM, CLIP)
• Support model fine-tuning and performance benchmarking
• Document experiments and results clearly
Agents Track
• Write, test, and refine prompts for agent workflows
• Help build and test tool-calling integrations
• Research and benchmark agent frameworks and orchestrators
• Assist in deploying agents to GPT Store or Copilot Studio
Multimodal (MLM) Track
• Explore and test vision-language models
(LLaVA, BLIP-2)
• Prepare multimodal datasets and evaluation sets
• Run inference pipelines and document outputs
RAG & Knowledge Track
• Support document ingestion, chunking, and embedding pipelines
• Test retrieval quality across different vector stores
• Experiment with chunking strategies and re-ranking methods
• Compare model performance across tasks (VQA, captioning)
• Help evaluate RAG pipeline accuracy and relevance
Cross-Track Responsibilities
Regardless of track, all interns will contribute to:
• Research & Benchmarking — survey latest models, tools, and papers summarize findings for the team.
• Prompt Writing & Testing — write, iterate, and evaluate prompts across different LLMs and tasks.
• Model Evaluation & Testing — run structured evaluations, log results, and identify failure patterns.
• Data Work — collection, cleaning, annotation, and quality checks as needed by the team.
• Documentation — write clear technical notes, how-to guides, and experiment logs.
• Team Collaboration — participate in standups, sprint planning, and design reviews.
Who We Are Looking For
Education
• Currently pursuing or recently completed a degree in Computer Science, AI, Data Science, Electronics, Mathematics, or a related field.
• Final-year students and fresh graduates are welcome to apply.
What Matters Most
• Curiosity — genuine interest in AI and willingness to go deep on problems.
• Logical thinking — ability to break down a problem and think through it step by step.
• Communication — can clearly explain what you tried, what worked, and what did not.
• Initiative — proactively looks for ways to contribute rather than waiting to be told.
• Coachability — open to feedback and fast to apply it.
What You Will Gain
• Real-world experience building and shipping AI systems — not just toy projects.
• Mentorship from ML/AI Engineers actively working on vision, agents, and multimodal systems.
• A strong portfolio of demonstrable work to show in future job applications.
• Exposure to the full AI product lifecycle — from idea to deployment.
• Certificate of completion and a performance-based letter of recommendation.
• Potential for a full-time offer based on performance during the internship.
#305/514, Hilton Centre, Sector 11, CBD Belapur,
Navi Mumbai 400614.
