AI Engineer - Healthcare
AI Nexus Innovations Hub · Bengaluru, Karnataka, India
Apply & track with Apply EdgeWe're Hiring: AI Engineer – Clinical AI for MedOrbit, an AI-Native Hospital PlatformThis 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 DetailsPosition: AI Engineer (Healthcare AI) – MedOrbit.ai
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 RoleYou 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 looks2️⃣ 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 outWhat You BringMust-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 productionNice-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 AIHow We WorkSmall 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 IndiaReady to Launch Your AI Career in Healthcare?Send your resume to: raju@thenexushub.aiWebsite: https://www.ainexushub.ai/ | https://medorbit.ai#Hiring #AIEngineer #Fresher #HealthcareAI #MedicalAI #ClinicalAI #ArtificialIntelligence #MachineLearning #DeepLearning #ComputerVision #MedicalImaging #DocumentAI #GenAI #LLM #RAG #Python #PyTorch #HealthTech #HMS #ABDM #FHIR #DICOM #Bangalore #Nagarabhavi #ImmediateJoiner #StartupJobs #FresherJobs #CareerGrowth #TechJobsDon't just graduate. Build clinical AI that doctors rely on. Transform healthcare. Grow exponentially.