Data Scientist

Role:

Location:

Role Overview

AI/ML Engineer

core AI engineering

Key Responsibilities

Computer Vision & Deep Learning

• Develop, train, and optimize deep learning models using

  PyTorch, TensorFlow, YOLO

  , or similar frameworks.
• Build and maintain

  image and video processing pipelines

  using

  OpenCV

  and classical CV techniques.
• Implement and optimize

  OCR pipelines

  and text extraction systems.
• Perform model optimization (quantization, pruning, ONNX/TensorRT conversions) for real-time performance.
• Develop complete data preprocessing workflows and scalable training pipelines.

Backend Engineering

• Develop backend services using

  Python (FastAPI/Flask)

  .
• Build REST APIs for ML inference, data processing, and workflow management.
• Integrate backend applications with databases such as

  MongoDB, SQL, NoSQL

  .
• Architect scalable microservices for ML and computer vision workloads.
• Work on logging, monitoring, and system stability for backend services.

MLOps, DevOps & Deployment

• Containerize and orchestrate applications using

  Docker

  and

  Kubernetes

  .
• Implement

  CI/CD pipelines

  for automated testing, deployment, and model updates.
• Deploy AI/ML workloads on

  cloud, on-premise, and edge computing platforms

  .
• Optimize infrastructure for high throughput and low-latency ML processing.

Required Skills

Core Technical Competencies

• Expert-level Python

  (mandatory).
• Strong experience with:

• PyTorch / TensorFlow / YOLO

• OpenCV & Image Processing

• OCR systems

• Docker, Kubernetes

• Git, GitLab, CI/CD tools

• MongoDB, SQL, NoSQL databases

• FastAPI or Flask

• Linux & Bash scripting (Optional)

Preferred Competencies

• Experience deploying ML/DL models on

  edge devices

  .
• Knowledge of ONNX, TensorRT, or hardware-level optimizations.
• Familiarity with real-time video/image streaming pipelines.
• Understanding of distributed systems or messaging technologies (Kafka, RabbitMQ, etc.).

Qualifications

• Bachelor’s or Master’s degree in

  Computer Science, Engineering, or related field

  .

• 1–2+ years

  of hands-on experience in AI/ML, Computer Vision, or MLOps.
• Proven experience building production-grade ML systems.

Soft Skills

• Strong analytical and debugging skills.
• Self-driven with the ability to own and deliver end-to-end solutions.
• Good communication and collaborative mindset.
• Passion for exploring new technologies in CV, ML, and systems architecture.