Machine Learning Engineer
Core
Building and deploying production-grade ML pipelines for image classification, detection, segmentation, and prompt-based generative modeling.
Role type
Machine Learning Engineer (Computer Vision & Generative AI)
Builds
Production ML pipelines, visual AI products, real-time/batch inference systems
Domain
Computer Vision, Generative AI, Image Processing
Deliverable
production ML models
Required skills
Python, PyTorch/TensorFlow, CNNs, Vision Transformers, diffusion models, image preprocessing/augmentation, model optimization (quantization/pruning/ONNX), GPU environment management
Preferred skills
ControlNet, LoRA, DreamBooth, TorchServe/FastAPI/Triton, cloud infrastructure (AWS/GCP), MLOps/CI-CD
Technologies
PyTorch, TensorFlow, OpenCV, albumentations, MLflow, Weights & Biases, ONNX, TensorRT, Docker, Stable Diffusion, DALLE, ControlNet
Responsibilities
Build and optimize ML pipelines for image tasks; Design, train, fine-tune, and deploy deep learning models; Work with image datasets including preprocessing and augmentation; Implement and integrate prompt-based generative models; Collaborate on deploying inference systems; Optimize model performance for speed, accuracy, and size; Ensure robust versioning, reproducibility, and monitoring of models
Seniority
Mid-level (2-4 years experience), hands-on IC