2 - 5 years

8 - 10 Lacs

Posted:Just now| Platform: Naukri logo

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Job Type

Full Time

Job Description

Role & responsibilities

  • AI Model Development: Design and implement DL models for document processing, diagram

detection, data extraction, and LLM-driven automation.

  • Geometric Transformations & Math: Apply advanced mathematical techniques (e.g.,

geometric transformations, linear algebra) to analyze and manipulate technical data.

  • Data Processing: Preprocess and annotate structured/unstructured datasets from technical

documents and diagrams.

  • Model Training & Deployment: Build and deploy models using C++, Python, and frameworks

like TensorFlow or PyTorch, ensuring scalability with Docker and Apache Airflow.

  • Pipeline Development: Create and maintain robust AI pipelines for data ingestion, model

training, and inference using Apache Airflow.

  • Collaboration: Work closely with AI engineers, software developers, and product managers to

integrate AI solutions into production systems.

  • Optimization: Enhance model performance for real-time applications, focusing on low-latency

and efficiency.

Key Requirements and Skills

  • Education: Degree in Computer Science, AI/ML, Mathematics, Engineering, or a related field.
  • Experience: 2-5 years in AI/ML development, with hands-on experience in document

processing, diagram detection, or similar technical domains.

  • Programming Skills: Strong proficiency in C++ and Python (e.g., NumPy, Pandas, OpenCV).
  • Familiarity with Rust is a plus.
  • Mathematics: Deep understanding of geometric transformations, linear algebra, and statistical

modelling.

AI/ML Expertise:

  • Experience with TensorFlow, PyTorch, or similar frameworks.
  • Knowledge of LLMs (e.g. GPT , Mistral , Llama ) and fine-tuning for domain-specific tasks.
  • Familiarity with Computer Vision (e.g., CNNs, object detection, image segmentation).
  • DevOps Tools: Proficiency in Docker for containerization and Apache Airflow for workflow

orchestration.

  • MLOps: Experience deploying ML models in production environments (e.g., AWS, Azure, or on

premises).

  • Problem-Solving: Ability to tackle complex challenges in technical data extraction and

automation.

Technical Skills

Must-Have:

  • Programming: C++, Python (TensorFlow, PyTorch, OpenCV).
  • AI/ML: LLMs, Computer Vision, model training, and deployment.
  • Tools: Docker, Apache Airflow, RESTful APIs.
  • Math: Geometric transformations, linear algebra, statistical methods.
  • Data: Preprocessing technical documents and diagrams.

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