
Unlock the Future of Biology
16 hours ago
About Us:
We are one of the world's fastest-growing AI companies, accelerating the advancement and deployment of powerful AI systems.
We help customers in two ways: working with leading AI labs to advance frontier model capabilities and leveraging that work to build real-world AI systems that solve mission-critical priorities for companies.
This role involves working on projects to fine-tune large language models using strong analytical and English comprehension skills.
- The ideal candidate should have a solid foundation in Biology, particularly at the PhD level.
- You should be able to break down complex biological concepts into simple clear explanations and work efficiently.
- This project will also help you learn how to leverage AI to be a better analyst.
Day-to-Day Tasks:
- Design and solve challenging Biology problems to probe the limitations of large language models.
- Develop high-quality step-by-step solutions with clear rigorous reasoning.
- Collaborate with LLM researchers to align problem types with evaluation goals especially in areas where models typically struggle.
- Contribute to defining new evaluation benchmarks based on Biology curricula spanning to PhD-level topics.
Requirements:
- Candidates pursuing a PhD/Postdoctoral degree in Biology Biotechnology Biochemistry or a related field are eligible and encouraged to apply.
- Good research and analytical skills.
- Ability to provide constructive feedback and detailed annotations.
- Creative and lateral thinking abilities.
- Excellent structured communication and collaboration skills in a remote setting.
- Self-motivated and able to work independently in a remote setting.
Benefits:
- Work in a fully remote environment.
- Opportunity to work on cutting-edge AI projects with leading LLM companies.
- Potential for contract extension based on performance and project needs.
Selection Process:
- Shortlisted experts may be asked to complete an assessment.
- If you clear the assessment, you will be contacted for contract assignments with expected start dates durations and end dates.
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