Machine Learning Engineer, Applied AI (Hybrid)
Tasks
- Build AI performance monitoring
- Champion experimentation and continuous learning
- Collaborate on scoping and planning
- Communicate milestones findings
- Conduct exploratory data analysis
- Customize data pipelines
- Design experiments and prototypes
- Design retrieval pipelines
- Develop AI workflows
- Engineer prompts
- Implement LLM evaluations
- Integrate AI workflows into production
- Integrate new ML techniques
- Leverage data to improve clinician workflows
- Mentor team members
- Optimize AI workflow performance reliability and scalability
- Provide AI expert advice to product and engineering
- Stay current with emerging ML tools
- Tune models
Perks/Benefits
- Employee resource groups
- Flexible time off
- Hybrid work schedule
- Meal reimbursement
- Paid Holidays
- Relocation bonus
- Work from home stipend
Skills/Tech-stack
AWS | Argo CD | Argo Workflows | CI/CD | Data Analysis | Data Engineering | Human-in-the-loop | Kubernetes | LLM evals | LLM orchestration | Machine Learning | Prompt engineering | Python | RAG | Retrieval-Augmented Generation | The Loop | Vector Databases
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
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