Machine Learning Engineer (Computer Vision – Model Engineering)
Core
Junior to Mid-Level Machine Learning Engineer building robust computer vision systems by managing the full model lifecycle from dataset preparation to optimization.
Role type
Junior to Mid-Level IC Machine Learning Engineer (Computer Vision)
Builds
Production-grade computer vision systems for real-world applications
Domain
Computer Vision / Machine Learning
Deliverable
production ML models
Required skills
Computer vision model training and fine-tuning, architecture development, experiment design and execution, Python, PyTorch or TensorFlow, Linux environments, data-centric approaches
Preferred skills
Custom model heads and loss functions, multimodal/vision-language/foundation models, model optimization (quantization/pruning/distillation), MLOps practices
Technologies
PyTorch, TensorFlow, Python, Linux
Responsibilities
Train, fine-tune, and evaluate models for classification, detection, segmentation, and pose estimation; optimize training strategies and architecture; prototype and benchmark new approaches; investigate edge cases to improve accuracy and efficiency; collaborate on dataset quality and system reliability
Seniority
Junior to Mid-Level, hands-on IC
