Tasks:
- * Apply reinforcement learning to audio processing
- * Build audio simulation environments
- * Collect audio data
- * Deploy models on edge devices
- * Design reward functions and policy networks
- * Maintain audio RL training and evaluation pipelines
- * Optimize compute usage
- * Quantize models
- * Train and evaluate models
- * Validate real time performance
Perks/Benefits:
Skills/Tech stack required:
[Acoustic features] [Actor-critic] [AEC] [ANC] [ARM NEON] [Audio signal processing] [CNN] [Conformer] [DDPG] [Deep learning] [Digital filters] [DSP] [ENC] [Linux] [MDP] [Model Quantization] [Policy gradients] [PPO] [Python] [PyTorch] [Reinforcement Learning] [RNN] [SAC] [Signal Processing] [Source separation] [Speech enhancement] [STFT] [Transformer]
Educational requirements:
[Doctoral degree] [Master's Degree]
Role(s):
[Audio Deep Learning Intern] [Deep Learning Intern] [Engineer Intern] [Intern] [Learning Intern] [Reinforcement Learning Engineer] [Reinforcement Learning Engineer Intern]