Computer Vision/Machine Learning Engineer

About the Role 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. What You'll Do • 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 Requirements Education • Bachelor's degree with 3+ years of experience, OR • Master's degree with 1+ year of experience, OR • PhD in a related field Technical Skills • 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 • Experience building and deploying models in real-world production environments • Familiar with edge/mobile AI scenarios or performance-constrained systems Soft Skills • 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 Have • Experience with mobile/edge deployment (iOS / Android) • Experience optimizing models for real-time applications • Background in performance-critical systems