Machine Learning Engineer
Tasks
- Architect model serving infrastructure and backend components
- Build scalable training evaluation and experimentation pipelines
- Collaborate with founders engineers and customers to translate workflows into ML solutions
- Deploy monitor and optimize ML models in production
- Design train optimize deep learning models
- Develop novel machine learning approaches for geometry and design data
- Establish best practices for experimentation logging model versioning performance monitoring
- Evaluate research in sequence modeling geometric deep learning representation learning foundation models
- Implement offline and online evaluation frameworks
- Own end to end ML lifecycle from research to deployment monitoring optimization
- Transform CAD and geometry data into training datasets
- Work with backend engineers on APIs infrastructure and data models
Perks/Benefits
- Career advancement
- Catered team lunches
- Equity ownership
- Growth opportunities
- Medical/Dental/Vision insurance
- Unlimited flexible paid time off
Skills/Tech-stack
AWS | Backend Services | CAD | Computational Geometry | Computer Graphics | Data Pipelines | Deep learning | Django | Experimentation | FastAPI | Flask | Foundation Models | GCP | Geometric Deep Learning | JAX | Logging | Machine Learning | Model Evaluation | Model Monitoring | Model Serving | Model Training | Model versioning | Offline evaluation | Online evaluation | PyTorch | Python | Representation Learning | Robotics | Sequence Modeling | TensorFlow | Training pipelines
Education
Regions
Countries
States
Cities
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