Computational Protein Engineer

OpenProtein.AI; United States; Remote; USD 90,000 - 160,000; Full time

Benefits offered by this job

Health insurance

Dental insurance

Equity

Job summary

OpenProtein.AI is seeking a technical customer success and education role to help researchers apply computational protein engineering methods on their projects. You will teach users, run demonstrations, onboard new customers, and create practical tutorials and case studies.

You will translate user feedback into product ideas, collaborate on feature design for both the front-end and APIs, and participate in conferences and customer visits to stay aligned with current research.

Qualifications

• Bachelor's degree plus industry or research experience, or a higher degree, in a quantitative field with a protein engineering background; a PhD is preferred.
• Broad knowledge of computational protein engineering, including protein language models, structure prediction, and sequence and structure design tools.
• Programming experience in Python, R, or a similar language.
• Familiarity with bioinformatics methods such as homology search, sequence alignment, structure analysis, phylogenetics, PSSMs, and HMMs.
• Understanding of deep learning and generative approaches, including autoregressive and diffusion models.
• Strong written, visual, and spoken communication, with an interest in teaching, learning, and collaborative work.

Responsibilities

• Teach users computational protein engineering practices and help them apply available tools to their projects.
• Lead product demonstrations, onboarding, tutorials, and other learning sessions.
• Create practical learning materials, including documentation, tutorials, and case studies.
• Build lasting customer relationships, identify pain points, and help shape solutions.
• Use the platform for internal work and translate firsthand experience and user feedback into product and feature ideas.
• Contribute to feature design across user-facing interfaces and backend APIs, implementation, research, and deployment.
• Represent the team at customer visits and conferences, and keep up with relevant research and laboratory techniques.

Skills

Python

R

Communication

Teaching

Education

Bachelor's degree in quantitative field

PhD preferred

Tools

TensorFlow

PyTorch

Job description

Role overview

Help researchers and other users apply computational protein engineering methods to their projects, while turning their feedback into improvements to a protein design platform. This role combines technical customer support and teaching with product discovery, feature design, implementation, and collaboration on research and deployment.

Responsibilities

• Teach users computational protein engineering practices and help them apply available tools to their projects.
• Lead product demonstrations, onboarding, tutorials, and other learning sessions.
• Create practical learning materials, including documentation, tutorials, and case studies.
• Build lasting customer relationships, identify pain points, and help shape solutions.
• Use the platform for internal work and translate firsthand experience and user feedback into product and feature ideas.
• Contribute to feature design across user-facing interfaces and backend APIs, implementation, research, and deployment.
• Represent the team at customer visits and conferences, and keep up with relevant research and laboratory techniques.

Requirements

• A bachelor’s degree plus industry or research experience, or a higher degree, in a quantitative field with a protein engineering background; a PhD is preferred.
• Broad knowledge of computational protein engineering, including protein language models, structure prediction, and sequence and structure design tools.
• Programming experience in Python, R, or a similar language.
• Familiarity with bioinformatics methods such as homology search, sequence alignment, structure analysis, phylogenetics, PSSMs, and HMMs.
• Understanding of deep learning and generative approaches, including autoregressive and diffusion models.
• Strong written, visual, and spoken communication, with an interest in teaching, learning, and collaborative work.

Nice to have

• Previous experience in a customer-facing role or implementing deep learning models from scratch.
• Hands-on antibody or enzyme engineering experience in a high-throughput, end-to-end setting.
• Frontend or backend software development experience, product or visual design skills, or experience with LLMs and retrieval-augmented generation.

Benefits and work setup

• Full-time, remote-friendly role, with the USA preferred.
• Base salary, equity, and health and dental insurance.