Machine Learning Engineer

📋 Description

• Develop distributed training pipelines for large datasets and models
• Build low-latency inference pipelines for real-time predictions
• Develop libraries to improve the performance of ML frameworks
• Maximize training/inference performance using GPU acceleration
• Design scalable model frameworks for high-volume trading data
• Collaborate with researchers to automate ML experiments, hyperparameter tuning, and retraining

🎯 Requirements

• 5+ years of experience in ML focusing on training or inference systems
• Real-time, low-latency ML pipelines in high-performance environments
• Strong engineering skills, including Python, CUDA, or C++
• Knowledge of ML frameworks such as PyTorch, TensorFlow, or JAX
• GPU programming for training/inference acceleration (CuDNN, TensorRT)
• Experience with distributed training for scaling ML workloads (Horovod, NCCL)