Senior Applied Scientist
Sydney, NSW, Australia
AUD 160K-200K (estimate) Senior-level Full Time
Tasks
- Apply reinforcement learning methods
- Build information retrieval systems
- Build multi GPU inference pipelines
- Build multi-GPU training pipelines
- Deploy ML and LLM systems
- Design training and evaluation datasets
- Develop automatic speech recognition systems
- Develop evaluation frameworks
- Develop natural language generation systems
- Develop natural language understanding systems
- Develop speech to text systems
- Develop text to speech systems
- Evaluate model quality and performance
- Extract knowledge from text
- Generate synthetic data
- Implement RLHF
- Implement mixed precision training
- Optimize inference performance
- Optimize latency throughput and memory
- Optimize model distillation and quantization
- Prototype ML and LLM systems
- Research ML and LLM systems
- Run A/B tests
- Train and fine-tune language models
- Train transformer based models
Perks/Benefits
- N/A
Skills/Tech-stack
A/B | A/B Testing | Actor-critic | B testing | Cost Optimization | Data Mining | Dataset generation | Distributed Training | Inference Optimization | Information Retrieval | Language Generation | Language Processing | Language Understanding | Latency optimization | Memory Optimization | Mixed Precision | Model Distillation | Multi-GPU | Natural Language | Natural Language Generation | Natural Language Processing | Natural Language Understanding | ONNX | PPO | PyTorch | Python | Quantization | Question Answering | RLHF | Reinforcement Learning | Rust | Speech Recognition | Speech-to-Text | Statistical modeling | Synthetic data | Text Classification | Text to Speech | Throughput Optimization | Transformer
Education
Regions
Countries
States
Cities
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