Machine Learning Engineer
Tasks
- Build and maintain traditional machine learning models
- Collaborate with full stack team on ML integration
- Deploy and serve machine learning models in production
- Develop and improve computer vision models
- Ensure reliable scalable production ML systems
- Monitor model quality and performance metrics
- Participate in ML lifecycle from experimentation to monitoring
- Use LLM APIs for structured outputs and evaluation workflows
Perks/Benefits
Skills/Tech-stack
Anthropic | AutoGluon | CUDA | CatBoost | Computer Vision | Docker | GCP | Gemini | Image analysis | Inference monitoring | LLM APIs | LightGBM | Mean Absolute Error | Model Packaging | Model Serving | NumPy | Object storage | OpenAI | Pandas | Prompt engineering | PyTorch | Python | R Squared | Regression evaluation | SciPy | Scikit-learn | Segmentation | Service Oriented | Service-Oriented Architecture | Temporal | XGBoost
Education
N/A
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