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Responsibilities

  • AI Solution Development
  • Design, develop, train, and deploy AI/ML models for: 
    • Video Analytics
    • Object Detection and Tracking
    • Facial Recognition
    • License Plate Recognition (LPR/ANPR)
    • Person Re-Identification
    • Behaviour Analytics
    • Multimodal AI applications
    • Generative AI and LLM-based solutions

  • Build end-to-end AI pipelines from data ingestion through model deployment and monitoring
  • Evaluate and benchmark state-of-the-art AI models and frameworks
  • Design and build user-facing application layers across the full CV lifecycle: data curation tools, training dashboards, evaluation, deployment workflows, and monitoring
  • Own backend services (Python, FastAPI, gRPC) that power automated CV pipelines—integrating data prep, augmentation, model training, and evaluation into seamless agent-driven workflows
  • Build scalable APIs with clean contracts, versioning, and documentation that internal teams and platform agents consume
  • Integrate and wrap CV toolkits (PyTorch, OpenCV, Ultralytics YOLO) so the platform can orchestrate them programmatically
  • Implement orchestration layers for multi-step pipelines with retry, rollback, and SLA guarantees

Requirements

  • Degree in Computer Science, Engineering, Information Technology, Data Analytics, Data Science, Image Processing or equivalent competencies
  • At least 3 years of experience in production deployment of AI solutionsCompetent in at least one programming language (e.g. Python, JavaScript,Java). Interest and ability to gain expertise in other programming languages, frameworks, and technologies
  • Able to contribute to architecting and engineering for AI would be a strong plus
  • Proven track record delivering AI projects from concept to deployment

Knowledge and experience with any of the following software engineering domains would be an advantage:
  • Web development
  • End-to-end implementation of production-grade solutions, optimized for scalability, stability and performance
  • Big data technologies
  • Container technologies
  • Data analytics, machine learning and artificial intelligence
  • Design, implement, and evaluate deep learning algorithms and models
  • Computer Vision foundational concepts
  • Vision-language models
  • Image preprocessing and retrieval (semantic and visual retrieval, detection, embeddings etc)
  • Video preprocessing and retrieval (temporal context, clip-level indexing) 
  • Resourceful and meticulous professionals who are passionate about delivering AI-powered capabilities