Machine Learning Engineer
Tasks
- Build and maintain traditional machine learning models for structured and sensor data
- Collaborate with full stack engineering team on ML integration
- Deploy package and serve machine learning models in production
- Develop computer vision models for vehicle crash analysis
- Ensure machine learning systems are reliable scalable and production ready
- Integrate LLM APIs for structured outputs and evaluation workflows
- Monitor model quality and performance metrics
- Participate in ML lifecycle from experimentation to deployment and monitoring
Perks/Benefits
Skills/Tech-stack
Anthropic API | AutoGluon | CUDA | CatBoost | Cloud platform | Computer Vision | Docker | Gemini API | Google Cloud | Google Cloud Platform | Google Gemini | Google Gemini API | Inference Serving | Language Models | Large Language Models | LightGBM | Model Evaluation | Model Monitoring | Model Packaging | NumPy | Object storage | OpenAI API | Pandas | Prompt engineering | PyTorch | Python | SciPy | Scikit-learn | Segmentation | Service Oriented | Service-Oriented Architecture | Temporal | XGBoost
Education
N/A
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