Machine Learning Engineer
Tasks
- Apply data augmentation
- Build microservices for model serving
- Build training pipelines
- Define evaluation benchmarks
- Deploy machine learning models
- Design deep learning models
- Distill knowledge
- Drive continuous improvement cycles
- Integrate models into production systems
- Manage dataset versioning
- Monitor model performance in production
- Optimize model inference
- Perform data preprocessing
- Prune models
- Quantize models
- Research deep learning models
- Serve models via APIs
- Train deep learning models
Perks/Benefits
Skills/Tech-stack
AWS SageMaker | Albumentations | Audio classification | Azure Machine Learning | CI/CD | Computer Vision | Convolutional Neural Networks | DDP | DETR | Deep learning | DeepSpeed | Diffusion Models | Distributed Training | Docker | ESPnet | EfficientNet | FSDP | Google Vertex | Google Vertex AI | Inference Server | JAX | Keras | Knowledge Distillation | Kubernetes | Librosa | Machine Learning | Model Pruning | Neural Networks | Noise suppression | ONNX Runtime | OpenCV | PyTorch | Python | Quantization | Recurrent Neural Networks | SAM | SQL | Speech Recognition | SpeechBrain | TensorFlow | TensorRT | Text to Speech | TorchAudio | TorchScript | Torchvision | Transformers | Triton Inference | Triton Inference Server | Vertex AI | ViT | Vision Transformers | Wav2Vec 2.0 | Whisper | YOLO
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
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