Lead Scientific Developer – Biologics & Protein Design

Location:

On-site in Santa Fe, NM.

Over the last eight years, Open Eye Scientific has developed the field’s most advanced large-scale compute platform, Orion, built on Amazon Web Services. In this position, you will be working at the cutting edge of cloud computing, C++/Python development, and advanced MD simulation techniques. Your work will have the potential to make a major impact in drug discovery and will be available to many pharmaceutical and biotech companies.

• Work on challenging problems and help find practical solutions that advance the field of computational biologics drug discovery
• Develop highly scalable and integrated solutions for biologics drug discovery in the cloud
• Develop data‑driven models using sequence and 3D molecular shape representations leveraging AI and physics‑based approaches
• Expand Open Eye’s biomolecular modeling and protein informatics technologies
• Collaborate with colleagues within our group, within Open Eye & Cadence, as well as within the broader pharmaceutical industry on developing new methods, tools, and solutions

• PhD (or equivalent experience) in computational chemistry, structural biology, biochemistry, or related field with at least 5 years relevant experience
• Strong desire to change the field of biologics drug discovery through hard work, creating robust software tools, and critical scientific evaluation
• Demonstrated ability to work both independently and as part of a team
• Ability to work humbly with others, admitting mistakes and constructively working through differences in opinion
• Experience with molecular dynamics simulations and machine learning
• Programming expertise, ideally in Python, preferably with experience using AI coding agents
• Proven track record of delivering software solutions

• Expertise with traditional machine learning and/or modern deep learning methods
• Experience with Open Eye software/toolkits or other computational chemistry toolkits
• Experience with protein language models and protein folding technologies
• Experience with modeling antibodies based on sequence and structural data