We're Hiring: AI Engineer – Clinical AI for MedOrbit, an AI-Native Hospital Platform

This isn't a "learn on a toy dataset" role. MedOrbit is already live with paying hospitals and already runs 11 AI agents in production under clinician control. You'll join to build the next ones – starting with lab-report intelligence and X-ray analysis – and see your models used by real doctors within weeks.

Role Details

Position: AI Engineer (Healthcare AI) – MedOrbit.ai

Location: Nagarabhavi, Bangalore (In office, 5 days a week)

Type: Full-time

Experience: 0 – 2 years

Joining: Immediate joiners strongly preferred

Mandatory: hands-on experience on at least one real healthcare AI project (academic, internship or personal, with a working demo)

About MedOrbit

MedOrbit (by AI Nexus Innovations Hub) is a multi-tenant hospital management platform built for Indian healthcare. One product serves 24 facility types – from a solo doctor's clinic to a 500-bed super-specialty hospital, a pathology lab, an imaging centre, a dialysis chain, a blood bank.

It runs the full clinical and operational spine: OPD, IPD, OT, Emergency, NICU, maternity, LIS / RIS / PACS, teleradiology, telemedicine, pharmacy, billing, revenue-cycle management and insurance / TPA.

It is ABDM-integrated (ABHA, consent, HIP/HIU, FHIR R4), NHCX-connected for claims, HL7 and DICOM interoperable, and carries the Indian regulatory surface – NABH/NABL evidence, DPDP consent and data-erasure.

And it is AI-native: 11 production agents already run under clinician control – an ambient scribe, pre-consult briefs, consult summaries with draft prescriptions, a result explainer for patients, referral triage, a claim-denial guard, a queue concierge, medication reconciliation, and voice agents on the front desk and in aftercare.

The Role

You will build clinical AI features that sit inside the doctor's consultation workflow – not a side dashboard. Your first two charters are already defined, and both ship into a live product:

1️⃣ Lab Report Intelligence

→ Build a pipeline that reads a patient's last 3 lab reports (digital and scanned PDFs) and extracts test values, reference ranges and units – across the report formats Indian labs actually produce

→ Generate a concise,



doctor-ready summary so the doctor doesn't have to open every past report during consultation

→ Build predictive summaries: trend lines across visits, deteriorating markers, cross-panel correlations and early-risk indicators that are easy to miss when reports are read one at a time

→ Produce AI-assisted consultation suggestions – discussion points for the patient, follow-up tests to consider, and what to monitor next

→ Wire the output into MedOrbit's existing pre-consult brief and consult-summary agents so it appears where the doctor already looks

2️⃣ AI-Assisted X-Ray Analysis

→ Train and fine-tune deep learning models on chest and other X-ray datasets to detect abnormalities and flag likely conditions

→ Build a "second pair of eyes" for the doctor – regions of interest, confidence scores and explainability (Grad-CAM / saliency maps), with clear "clinician must review" handling

→ Integrate with the RIS / PACS module so findings appear on the imaging report inside the HMS, with DICOM in and structured findings out

What You Bring

Must-Have:

→ B.Tech / B.E. / M.Tech / M.S. in Computer Science, AI/ML, Data Science, Biomedical Engineering, or related field (2024–2026 batches welcome)

→ Hands-on experience on at least one real healthcare AI project – lab/medical report extraction, medical imaging (X-ray / CT classification or segmentation), clinical NLP, or EHR / HMS data.

→ Strong fundamentals in Python and at least one ML framework (PyTorch, TensorFlow, or scikit-learn)

→ Understanding of ML concepts: supervised/unsupervised learning, CNNs, transfer learning, NLP basics, evaluation metrics (precision/recall, AUROC, calibration)

→ Familiarity with Generative AI, LLMs, prompt engineering or RAG

→ Comfort reading an API contract and integrating a model into a service someone else built

→ Solid problem-solving skills,



a builder's mindset and excellent communication – you'll talk to doctors, not just engineers

→ Self-starter mentality – comfortable in a fast-paced startup shipping continuously to production

Nice-to-Have (Bonus Points!):

→ Experience with OCR / document AI tools (Tesseract, PaddleOCR, AWS Textract, Azure Document Intelligence, LayoutLM / Donut)

→ Familiarity with public medical imaging datasets (NIH ChestX-ray14, CheXpert, MIMIC-CXR, VinDr-CXR) and medical imaging libraries (MONAI, torchxrayvision, pydicom)

→ Experience with LangChain / LangGraph, Hugging Face, OpenAI / Anthropic / Gemini APIs, vector databases

→ Exposure to speech / voice AI (ASR, TTS) or Indian-language NLP

→ AWS, Docker, Git, CI/CD pipelines

→ Kaggle competitions, open-source contributions, or published work in medical AI

How We Work

Small team, short decision path, direct access to the founders. Specifications are written down and taken seriously. We ship continuously to a live production platform, and AI features are validated with clinicians in hospitals, not in a conference room.

Why Join AI Nexus?

✅ Skip the corporate queue: build production clinical AI from Day 1 on a platform that is already live – no waiting for "the product" to exist

✅ Real stakes – your models assist real doctors and real patients across 24 facility types

✅ A mature AI stack to build on: 11 agents in production, ABDM / FHIR / DICOM integration already done

✅ High-end MacBook provided

✅ Fast-track career growth in a high-potential deep-tech startup

✅ Build products that improve healthcare delivery across India

Ready to Launch Your AI Career in Healthcare?

Send your resume to: [email protected]

Website: https://www.ainexushub.ai/ | https://medorbit.ai

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Don't just graduate. Build clinical AI that doctors rely on. Transform healthcare. Grow exponentially.

📌 AI Engineer - Healthcare (Bengaluru)
🏢 AI Nexus Innovations Hub
📍 Bengaluru