Large Language Model
LLM, Developer
Posted on 3/23/2023
INACTIVE
Provides tools for designing and manufacturing biological cells
Company Overview
Asimov's unique approach to biotechnology, integrating synthetic biology, computer-aided design, and machine learning, positions it as a leader in the design and manufacture of biologics and gene therapies. The company provides comprehensive support to its clients, offering both the tools for in-house cell line development and a service to create custom cell lines, demonstrating a commitment to flexibility and customer needs. Asimov's culture fosters interdisciplinary collaboration, driving technical advancements and enhancing its competitive edge in the biotech industry.
Biotechnology
B2B
Company Stage
Series B
Total Funding
$204.7M
Founded
2017
Headquarters
Boston, Massachusetts
Growth & Insights
Headcount
6 month growth
↑ 19%1 year growth
↑ 39%2 year growth
↑ 134%Locations
Dorchester, Boston, MA, USA
Experience Level
Entry
Junior
Mid
Senior
Expert
Desired Skills
Python
Data Science
R
Natural Language Processing (NLP)
CategoriesNew
AI & Machine Learning
Biology & Biotech
Requirements
- Master's degree or Ph.D. in computer science, artificial intelligence, or a related field
- 3+ years of experience in natural language processing, machine learning, and/or data science
- Experience working with large language models, such as GPT-3+, LLAMA, or similar
- Experience working in synthetic biology or a related field is preferred
- Strong communication skills and the ability to work in a team environment
- Strong problem-solving skills and the ability to think creatively to identify new opportunities for LLMs in our products and services
- Proficiency in programming languages such as Python or R
- Familiarity with cloud-based infrastructure and distributed computing
Responsibilities
- Develop and integrate LLMs into our software products, enabling natural language queries and responses to facilitate user interaction
- Use LLMs to distill information from the scientific literature, providing summaries and key takeaways for genetic designers
- Create educational content for genetic designers, using LLMs to generate interactive tutorials, case studies, and best practices
- Enable greater intra-organization knowledge retrieval using LLMs, allowing team members to quickly find relevant information and insights from past experiments and other organizational documents
- Collaborate with our team of genetic designers and software developers to identify new opportunities for LLMs in our products and services