Junior AI Engineer – Applied AI (Non-Clinical)
Teleradiology Solutions (company site, opens in a new tab)2–4 yrsBengaluruOn-siteDirect career pageEst. 12–22 LPA
Posted 1d ago
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Job description
Structured overview of role & requirements
About This Role
- Build, train, and deploy operational ML models for case routing, prioritization, TAT prediction, scheduling, and volume forecasting in a 24x7 teleradiology service.
- Develop AI-enabled features for mobile applications (React Native, Flutter, native iOS/Android) integrated with backend ML services.
- Package and ship production-grade ML services using Python, Docker, FastAPI, with unit and regression testing under senior engineer guidance.
Minimum Requirements
- 2-4 years hands-on experience in software and ML engineering, including mobile apps and ML systems deployed to real users.
- Education: B.Tech/B.E./M.Tech/MS/M.Sc. from IIT, IISc, IIIT, BITS Pilani or comparable in CS, ECE, AI, Data Science, Mathematics, Statistics, or related quantitative field with strong academics.
- Strong Python programming with hands-on experience in ML libraries like scikit-learn, XGBoost, LightGBM and production ML deployments.
- Regular use of Claude Code or similar AI-assisted coding tools with solid testing and review of AI-generated code.
Ideal Candidate Profile
- Has built and shipped at least one full mobile app or ML project personally, demonstrating deep technical expertise and ownership.
- Experience with tabular/time-series data, gradient-boosted models, forecasting, and optimization problems relevant to operational workflows.
- Comfortable working with operational data pipelines, defining success metrics with stakeholders, and measuring model impact in production environments.