AI Engineer
Tasks
- Build applied AI systems end to end
- Build evaluation datasets and benchmarks
- Collaborate on CV training and deployment
- Create confidence aware AI outputs
- Define metrics for model quality
- Develop models and inference pipelines
- Estimate event likelihood and fan interest
- Handle multimodal sports data
- Implement human review correction workflows
- Integrate AI outputs into real time products
- Mentor junior teammates and run experiment design
- Perform event detection and prediction
- Train adapt evaluate and integrate ML models
Perks/Benefits
Skills/Tech-stack
Computer Vision | Data Quality | Data labeling | Deep learning | Evaluation metrics | Event Detection | Inference Pipelines | LLM APIs | Language Models | Language Processing | Large Language Models | Machine Learning | Multimodal modeling | Natural Language | Natural Language Processing | Observability | Performance Engineering | Predictive Modeling | Reliability Engineering | Rust | Streaming Data | Uncertainty Estimation
Education
N/A
Roles
AI | AI Engineer | Engineer
Regions
Countries
States
Cities
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