Computational Protein Engineer

At OpenProtein.AI, we are decoding the fundamental language of proteins to transform biological discovery and design. Our cloud-based SaaS platform enables biologists, bioinformaticians, and ML engineers across leading pharmaceutical companies, biotechs, and innovative startups to predict variant effects, optimize protein function, design novel proteins de novo, and accelerate design-build-test cycles with unprecedented data efficiency. We are building the next generation of protein foundation models, harnessing billions of years of evolution to break conventional scaling laws and deliver 20x superior design outcomes and 3x higher success rates with as few as tens of training examples. Join us in building the future of AIxBiology.

• Work closely with users to teach them best practices in modern protein engineering, how to use our platform, and collaborate with them on their projects to ensure customer success
• Run demos, tutorial and onboarding sessions, and other teaching activities
• Write case studies, documentation, tutorials, etc.
• Cultivate long-term customer working relationships, understand customer pain points, and engage in developing solutions
• Use our platform and other available tooling for internal projects, be the #1 user, and use that experience to inform product roadmap and design of new features and products
• Lead ideation and design of new features, including front end and backend API design, and assist with implementation especially for user-facing components, building on customer feedback
• Collaborate in new research activities and deployment of those features
  
• Stay up to date with the latest research, models, algorithms, and wet lab techniques
  
• Visit customers and represent OpenProtein.AI at conferences and other venues
  

• Bachelors with industry or research experience or higher degree (PhD preferred) in a quantitative field with a background in protein engineering
• Complete knowledge of the modern computational protein engineering stack from protein language models to structure prediction models to structure and sequence design tools and concepts. Know and be familiar with the suite of cutting edge models and be able to discuss their use cases and pros and cons of different algorithms across protein engineering problems (e.g., binder design, enzyme design, protein optimization, etc.)
• Knowledge of wet lab techniques for general protein engineering, e.g., mutational scans, affinity selection assays, structure determination methods, biophysical characterization methods, etc.
• Experience with Python, R, or a similar programming language
• Experience with the general bioinformatics toolkit: homology search, sequence alignment algorithms, structure analysis tools, phylogenetics, PSSMs, HMMs, etc.
• Familiarity with deep learning and generative modeling techniques like autoregressive or diffusion-based models
• Strong communication skills in written, visual, and oral form with demonstrated ability
  
• Enjoy teaching, learning, and have a collaborative mindset
  

• Previous experience in a client-facing role
• Experience implementing deep learning models from scratch
• Hands on experience with antibody engineering or enzyme engineering in a high throughput end-to-end setting
• Front end or back end software engineering experience
• Strong product and visual design sense
• Experience deploying and using LLMs and RAG solutions

• Competitive base salary and equity
• Health and dental insurance