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

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