AI Engineer

Teleradiology Solutions; Bengaluru; On-site; INR 1,200,000 - 2,000,000; Full time

Job summary

Teleradiology Solutions, Bengaluru-based on-site AI role, seeks an AI Engineer with 2+ years of experience to build production-grade GenAI/LLMs, OCR, and computer vision systems. You will design, train, and deploy models, expose services via FastAPI, and containerize with Docker for scalable deployments.

You will work across the stack with cross-functional teams, implement data pipelines with MongoDB/SQL, and integrate multiple LLM providers.

Qualifications

• 2+ years of AI/ML engineering experience.

Responsibilities

• Design, develop, and deploy GenAI/LLM-based solutions (RAG pipelines, embeddings, fine-tuning)
• Build and optimize OCR pipelines for document/data extraction
• Develop and fine-tune Computer Vision models for classification, detection, and segmentation
• Develop and maintain RESTful APIs using FastAPI to expose AI/ML models
• Containerize applications with Docker and manage deployment across environments
• Design data storage with MongoDB and SQL databases
• Integrate LLM APIs (OpenAI, Claude, LLaMA/Mistral) into production apps
• Work with vector databases (FAISS, Pinecone, Chroma, Weaviate) for semantic search
• Collaborate with product/backend/DevOps to integrate AI features
• Write clean, testable code and monitor model performance in production
• Stay updated on GenAI, OCR, and CV advancements

Skills

Python

GenAI / LLMs

OCR technologies

Computer Vision

FastAPI

Docker

MongoDB

SQL databases

REST API design

Git

CI/CD

Tools

PyTorch

TensorFlow

OpenCV

LangChain

Job description

Job Description -AI Engineer

About Company:

Teleradiology Solutions (TRS) is a pioneer in teleradiology, delivering round-the-clock diagnostic radiology reporting and support to hospitals and healthcare providers across India, the US, and other global markets. Founded in 2002 by two Yale-trained physicians and headquartered in Ardmore, PA, TRS today serves over 150 hospitals across 21 countries.

The company pairs a network of board-certified radiologists — including ABR-certified specialists — with technology-driven workflows and its AI-enabled arm, dAIgnostiX, to deliver fast, accurate, and reliable imaging interpretation. dAIgnostiX is based out of Bengaluru (Whitefield). TRS/dAIX also maintains an active academic focus (www.radguru.net) and ongoing research interests, including AI in radiology.

Experience: 2+ Years

Location: Bengaluru / On-site

Department: Artificial Intelligence

About the Role

We are looking for a hands-on AI Engineer with 2+ years of experience to design, build, and deploy production-grade AI systems, with strong focus areas in Generative AI / LLMs, OCR-based document/data extraction, and Computer Vision (classification, object detection, segmentation). The ideal candidate is comfortable working across the full stack — from model development/integration to backend APIs to deployment.

Key Responsibilities

• Design, develop, and deploy GenAI/LLM-based solutions (RAG pipelines, prompt engineering, fine-tuning, agentic workflows).
• Build and optimize OCR pipelines for extracting structured data from scanned documents, PDFs, images, and forms.
• Develop, train, and fine-tune Computer Vision models for image classification, object detection, and segmentation tasks.
• Develop and maintain RESTful APIs using FastAPI to expose AI/ML models and services.
• Containerize applications using Docker and manage deployment across environments.
• Design and manage data storage using MongoDB (NoSQL) and SQL databases.
• Integrate LLM APIs (OpenAI, Anthropic Claude, open-source LLMs like LLaMA/Mistral) into production applications.
• Work with vector databases (FAISS, Pinecone, Chroma, Weaviate, etc.) for semantic search and RAG implementations.
• Collaborate with cross-functional teams (product, backend, DevOps) to integrate AI features into existing platforms.
• Write clean, maintainable, well-documented, and testable code.
• Monitor model performance, debug issues, and iterate on solutions based on production feedback.
• Stay current with advancements in GenAI, LLMs, OCR, and Computer Vision.

Required Skills & Qualifications

• 2+ years of experience in AI/ML engineering.
• Strong proficiency in Python.
• Hands‑on experience with GenAI / LLMs — prompt engineering, RAG, embeddings, fine‑tuning, or agentic frameworks (LangChain, LlamaIndex, LangGraph or similar).
• Practical experience with OCR technologies (Tesseract, PaddleOCR, AWS Textract, Google Vision OCR, Azure Form Recognizer, or similar) for document/image data extraction.
• Hands‑on experience with Computer Vision — image classification, object detection (YOLO, Faster R‑CNN, etc.), and segmentation (U‑Net, Mask R‑CNN, semantic/instance segmentation) using frameworks like PyTorch, TensorFlow, or OpenCV.
• Solid experience building APIs with FastAPI.
• Working knowledge of Docker — building images, writing Dockerfiles, docker‑compose.
• Experience with MongoDB and SQL databases (schema design, queries, indexing, aggregation).
• Understanding of core ML/DL concepts (CNNs, transformers, embeddings, evaluation metrics like IoU, mAP, F1).
• Familiarity with version control (Git) and basic CI/CD practices.
• Good understanding of REST API design principles and asynchronous programming in Python.

Good to Have

• Experience with vector databases and semantic search.
• Exposure to cloud platforms (AWS/Azure/GCP), especially their AI/ML and storage services.
• Experience with model training/fine‑tuning pipelines (Hugging Face, PyTorch, Detectron2, MMDetection).
• Familiarity with medical imaging formats (DICOM) or other domain‑specific imaging pipelines.
• Familiarity with message queues (RabbitMQ/Kafka) for async processing.
• Experience with monitoring/logging tools for production AI systems.
• Prior experience in healthcare, fintech, or document‑heavy domains is a plus.

Soft Skills

• Strong problem‑solving ability and willingness to work across the stack.
• Ability to work independently and in a fast‑paced, iterative environment.
• Good communication skills to collaborate with cross‑functional teams.