Senior Applied Machine Learning Engineer, Typographic Intelligence
Tasks
- Build training pipelines for data ingestion and feature engineering
- Implement model monitoring for drift and data quality
- Integrate models into client and server architectures using APIs and services
- Model typographic layout and styling
- Optimize training and inference for latency and scalability
- Perform model debugging and error analysis
- Productionize models and deploy inference services
- Prototype generative approaches and apply reinforcement learning or bandit methods
- Train and validate machine learning models
- Tune hyperparameters for performance and robustness
- Write production code tests and automation
Perks/Benefits
- N/A
Skills/Tech-stack
APIs | Adversarial Networks | Bandit Algorithms | CI/CD | Data Pipelines | Data Quality | Deep learning | Diffusion Models | Error Analysis | Feature Engineering | Generative Adversarial Networks | Hyperparameter Tuning | Knowledge Distillation | Machine Learning | Mixed Precision | Model Debugging | Model Drift | Model Serving | Monitoring | Multimodal Transformers | Pruning | PyTorch | Python | Quantization | Reinforcement Learning | TensorFlow | Version control
Education
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