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 robust 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.

📌 AI Engineer (Bengaluru)
🏢 Important Group
📍 Bengaluru