AI Engineer (Middle/senior/leader)

Core Requirements
● Strong engineering background with proficiency in Python and deep learning frameworks
(PyTorch, TensorFlow, Unsloth, or similar).
● Solid understanding of core ML/AI concepts and mathematics (linear algebra, probability,
optimization).
● Experience deploying AI/ML models in production environments.
● Familiarity with one or more of the following areas:
○ Computer Vision: object/behavior detection, re-identification, segmentation, or
diffusion-based models.
○ NLP: transformers, RAG pipelines, large language models, conversational AI, or text
understanding for diverse applications.
○ Agentic AI Systems: tool-using agents, multi-agent coordination, or autonomous
workflows.
○ Multi-Domain AI: experience adapting AI solutions across different verticals (urban
tech, consumer apps, enterprise systems).
Bonus Points
● Experience across multiple domains such as smart cities (traffic analytics, surveillance, sensor
data, public safety), consumer applications (recommendation systems, personalization, user
experience), or enterprise intelligent systems.
● ML Ops knowledge: MLflow, W&B, Docker, cloud compute (AWS, GCP, etc.).
● Exposure to distributed training or large-scale data processing.
● Experience with API development, microservices architecture, or full-stack AI integration.
● Contributions to research papers or open-source ML libraries.