Transforming the logistics industry by automating freight appointment scheduling for brokers and carriers using agentic AI to improve efficiency and reduce CO2 emissions.
Requirements
- ML models
- natural language processing
- LLM applications
- RAG
- fine-tuning
- data-driven prompt engineering
- Python
- MLOps on AWS
Responsibilities
- Build, deploy, fine-tune, and maintain AI production systems to support enterprise-grade production use cases with 99%+ uptime and accuracy within 3 months.
- Develop tools to support continuous improvement of AI production systems, including: Performance monitoring
- A/B prompt testing
- Training dataset development for model fine-tuning
- RLHF
- Act as a force multiplier for the entire engineering team.
- Support and mentor other engineers on AI systems and industry best practices
Other
- Opportunity for equity ownership in a remote-first startup.
- This role is the first hire in the US and comes with the opportunity for meaningful equity ownership.
- Help recruit additional AI engineers in the US
- Co-author public-facing thought leadership and technical content
- Become one of the top experts in freight appointment scheduling data and processes within 6 months.
