AI Engineer

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.