AI Engineer

Teleradiology Solutions; Arishinakunte; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Teleradiology Solutions (TRS) in Bengaluru is seeking an AI Engineer with 2+ years of hands-on experience to design, build, and deploy production-grade AI systems focused on GenAI/LLMs, OCR data extraction, and computer vision.

You will work across the full stack—from model development and backend APIs to deployment—building scalable solutions and integrating with FastAPI, Docker, and databases while collaborating with product and DevOps teams.

Qualifications

• 2+ years of experience in AI/ML engineering.
• Strong proficiency in Python.
• Hands-on GenAI/LLMs—prompt engineering, RAG, embeddings, fine-tuning.
• Experience with OCR technologies for document/data extraction.
• Experience with Computer Vision: classification, detection, segmentation using PyTorch/TensorFlow/OpenCV.
• Experience with FastAPI to build APIs.
• Docker experience and Dockerfiles/docker-compose.
• Experience with MongoDB and SQL databases.
• Understanding of ML/DL concepts (CNNs, transformers, IoU, mAP).
• Version control with Git; basic CI/CD.

Responsibilities

• Design, develop, and deploy GenAI/LLM-based solutions.
• Build and optimize OCR pipelines for structured data extraction.
• Develop and fine-tune computer vision models for classification/detection/segmentation.
• Develop and maintain RESTful APIs with FastAPI.
• Containerize applications with Docker and manage multi-environment deployment.
• Design data storage schemas in MongoDB and SQL.
• Integrate LLM APIs (OpenAI, Claude, open-source LLMs).
• Work with vector databases (FAISS, Pinecone, Weaviate).
• Collaborate with product, backend, and DevOps teams.
• Write clean, well-documented, testable code.
• Monitor model performance and iterate based on feedback.
• Stay updated on GenAI, OCR, and CV advances.

Skills

Python

GenAI / LLMs

Prompt engineering

OCR

Computer Vision

REST APIs

Docker

MongoDB

SQL databases

FastAPI

Git

CI/CD basics

Tools

PyTorch

TensorFlow

OpenCV

LangChain

LlamaIndex

LangGraph

FAISS

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.