Position: AI Intern
Location: Hybrid
Employment Type: 3-month internship, with potential transition to part-time and full-time based on performance.
Company Description
At SETV Healthcare Technologies Private Limited, we believe healthcare deserves a different kind of intelligence, one that understands context, respects uncertainty, and supports human judgment. We don’t build systems that simply generate answers. We build systems that think with you. With Meddollina.ai, we are redefining how technology assists clinicians, prioritizing safety, precision, and trust over speed.
We design technology to feel natural, seamless, and essential. By bringing together AI, real-time data systems, and interoperable standards, we create platforms that integrate effortlessly into clinical workflows. Our goal isn’t to replace decision-making, it’s to elevate it. Because the future of healthcare isn’t just faster, it’s smarter, more reliable, and deeply human.
Duties and Responsibilities
- Prepare, clean, and version datasets for model training and evaluation
- Run and log model experiments in a structured, reproducible format
- Support LLM fine-tuning and prompt engineering workflows
- Build and execute benchmarking pipelines and document results
- Evaluate inference pipelines and flag failure modes or regressions
- Contribute to applied research tasks and internal technical documentation
Requirements
- Strong analytical thinking and ability to reason through model behaviour and data problems
- Python proficiency with working knowledge of at least one ML framework (PyTorch, HuggingFace, TensorFlow, or similar)
- Comfortable designing and executing data cleaning and preprocessing pipelines
- Ability to design controlled experiments, track variables, and document results reproducibly
- Clear written communication for technical summaries, experiment logs, and findings reports
- Ability to onboard into an unfamiliar codebase and contribute meaningfully within two weeks
Preferred Skills
- Understanding of how models are served in production, API design, latency, and scaling
- Hands-on deployment experience via Render, Railway, or similar platforms
- Familiarity with experiment tracking tools (MLflow, W&B), model versioning, and CI/CD for ML
- Prior structured work with prompt engineering, chain-of-thought design, or RAG pipelines
- GitHub projects, Kaggle contributions, or published technical writing demonstrating independent initiative
Qualifications
Pursuing or recently completed:
- Computer Science / AI / Machine Learning
- Data Science / Statistics / Mathematics
- Any engineering discipline with strong ML coursework
Stipend & Growth
- First 3 months : Learning + evaluation phase
- Post 3 months : Paid part-time role based on demonstrated performance
- Early conversion possible for high-performing interns
- Performance is evaluated on quality of deliverables, not time served
Selection Process (3 Rounds)
- Application – Resume.
- Technical Round – A short data cleaning or model evaluation exercise assessed on code quality, documentation, and reasoning.
- HR Round – Evaluation of communication, commitment, and role fit.
What We Offer
- Hands-on experience building AI systems in a real-world healthtech product
- Exposure to LLM infrastructure, fine-tuning, and evaluation workflows
- Hybrid work setup with direct mentorship from the Lead AI Engineer
- Growth based on performance, output quality, and impact
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