About The Position

We are looking for a Computer Vision / Machine Learning Engineer to join a fast-growing, product-driven team working on real-world AI applications. This role focuses on building and optimizing lightweight visual models for production environments, with strong emphasis on performance, efficiency, and deployment.

Requirements

  • Bachelor's degree with 3+ years of experience, OR Master's degree with 1+ year of experience, OR PhD in a related field
  • Strong foundation in Computer Vision and Machine Learning
  • Experience with model optimization for production (latency, memory, power trade-offs)
  • Hands-on experience with lightweight model deployment (e.g., ONNX, TFLite, CoreML)
  • Experience with model compression techniques (quantization, pruning, distillation)
  • Solid programming skills (Python + ML frameworks such as PyTorch or TensorFlow)
  • Experience building and deploying models in real-world production environments
  • Familiar with edge/mobile AI scenarios or performance-constrained systems
  • Strong problem-solving ability and ownership mindset
  • Comfortable working in a fast-paced, high-growth environment
  • Able to independently drive projects end-to-end

Nice To Haves

  • Experience with mobile/edge deployment (iOS / Android)
  • Experience optimizing models for real-time applications
  • Background in performance-critical systems

Responsibilities

  • Model Selection
  • Choose the most suitable approaches (traditional algorithms vs. deep learning) based on real-world use cases and constraints
  • Performance Optimization
  • Optimize models by balancing accuracy, latency, memory, and power consumption
  • Model Training & Compression
  • Train and optimize lightweight models using techniques such as quantization, pruning, and knowledge distillation
  • Deployment & Optimization
  • Deploy models to production environments (mobile/edge), ensuring low latency and high efficiency
  • End-to-End Ownership
  • Drive the full lifecycle from data analysis model development optimization deployment
  • Application Performance
  • Improve overall application responsiveness and resource usage to ensure smooth user experience
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