Machine Learning Engineer
Tasks
- Build training pipelines for large scale datasets
- Define evaluation benchmarks and monitor performance
- Design model serving APIs and microservices
- Drive continuous improvement cycles
- Integrate models into production systems
- Optimize models for inference latency throughput memory
- Perform data preprocessing augmentation and versioning
- Research and design deep learning models
- Train and productionize deep learning models
Perks/Benefits
- Leadership development programs
- Learning and development programs
- Multicultural experience
- Open minded collaborative culture
- Professional growth
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 | GCP Vertex | GCP Vertex AI | Image Segmentation | Inference Server | JAX | Keras | Knowledge Distillation | Kubernetes | Librosa | Machine Learning | Model Pruning | Model Quantization | Neural Networks | Noise suppression | ONNX | ONNX Runtime | Object Detection | OpenCV | PyTorch | Python | RNN | SQL | Segment Anything | Segment Anything Model | Speech Recognition | SpeechBrain | TensorFlow | TensorRT | Text to Speech | TorchAudio | TorchScript | Torchvision | Transformers | Triton Inference | Triton Inference Server | Vertex AI | ViT | Video Understanding | Wav2vec | Whisper | YOLO
Education
Bachelor of Engineering | Bachelor of Science | Master of Engineering | Master of Science | PhD
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