Machine Learning Engineer, Applied AI
Tasks
- Bridge research and product to deploy models
- Build and ship ML products
- Collaborate with product to define success criteria
- Create and curate datasets
- Design benchmarks and evaluation metrics
- Fine tune and deploy generative models
- Implement safety monitoring and reliability systems
- Label and clean datasets
- Lead zero to one applied ML projects
- Run error analysis and debug numerical stability
- Set client success metrics for quality latency cost
Perks/Benefits
- Autonomy to experiment
- Dental insurance
- Employer retirement plan match
- Health insurance
- In office lunches and dinners
- Learning and growth opportunities
- Mentorship
- Vacation
- Vision insurance
Skills/Tech-stack
Data labeling | Dataset curation | Diffusion Models | Error Analysis | Evaluation metrics | JAX | Model Evaluation | Multimodal Learning | Numerical Stability | PyTorch | Python | Transformers
Education
N/A
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