Senior Applied AI Engineer
Tasks
- Build data pipelines
- Build datasets and evaluations
- Build tooling for clinical reviewers
- Build training infrastructure
- Conduct offline benchmarks
- Conduct online experiments
- Design build train evaluate improve ML and LLM systems
- Develop evaluation frameworks
- Implement monitoring and guardrails
- Lead AI initiative execution
- Manage prompts and models
- Mentor engineers and raise engineering rigor
- Productionize model inference
- Run human in the loop review
- Scope ML problems with clinicians and product partners
- Translate clinical requirements into ML requirements
Perks/Benefits
- 401k matching
- Flexible work schedule
- Medical/Dental/Vision insurance
- Paid time off
- Parental leave
- Remote-first
Skills/Tech-stack
Data Pipelines | Distributed inference | Fine Tuning | Guardrails | Human-in-the-loop | Inference infrastructure | Language Models | Large Language Models | Machine Learning | Model Evaluation | Monitoring | Offline Benchmarking | Online Experimentation | Prompting | Python | Retrieval-Augmented Generation | The Loop | Training Infrastructure
Education
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