Scientific Software Engineer, AISim

About SandboxAQ

SandboxAQ is a high-growth company delivering AI solutions that address some of the world's greatest challenges. The company’s Large Quantitative Models (LQMs) power advances in life sciences, financial services, navigation, cybersecurity, and other sectors.

We are a global team that is tech-focused and includes experts in AI, chemistry, cybersecurity, physics, mathematics, medicine, engineering, and other specialties. The company emerged from Alphabet Inc. as an independent, growth capital-backed company in 2022, funded by leading investors and supported by a braintrust of industry leaders. 

At SandboxAQ, we’ve cultivated an environment that encourages creativity, collaboration, and impact. By investing deeply in our people, we’re building a thriving, global workforce poised to tackle the world's epic challenges. Join us to advance your career in pursuit of an inspiring mission, in a community of like-minded people who value entrepreneurialism, ownership, and transformative impact. 

About the Role

Our team is seeking a Scientific Software Engineer to develop and maintain AI-accelerated computational chemistry tools, enabling breakthrough solutions for materials discovery. This role places you at the heart of pioneering advancements, where you'll be instrumental in advancing cutting-edge AI-powered material discovery software including sophisticated agentic AI systems focused on tasks like automated catalyst design. You will be working at the exciting intersection of physics-based simulations, advanced machine learning, generative AI, large-scale data processing, and massively parallel computing. As our portfolio of capabilities expands, leveraging these cutting-edge areas and modern deep learning architectures, we require reliable, efficient, and scalable software to drive our AI-driven scientific explorations.

We are looking for an experienced engineer to create robust and maintainable software by collaborating closely with computational chemists, physicists, AI experts, and software engineers to transform scientific prototypes into scalable products that redefine materials science.

What You’ll Do

• Maintain and extend existing scientific software packages, and drive the full lifecycle of new ones
• Architect and implement cutting-edge scientific and ML software alongside subject matter experts
• Adopt current practices and ensure stability through testing
• Accelerate use of these packages through AI agents
• Work closely with the client-facing Material Discovery Team to identify needs and help with technical challenges
• Improve prototypes of novel scientific tools to overcome bottlenecks and instabilities.
• Offer oversight and guidance for performing mission-critical computational scientific work
• Provide clear and up-to-date documentation
• Work closely with the Engineering Team to build on top of the group’s cloud infrastructure
• Manage dependencies and integrate software into CI/CD pipelines
• Adapt software to different commercial cloud backends
• Foster a work culture of curiosity and kindness

About You

• Degree in a relevant scientific discipline (for example computer science, computer engineering, physics, chemistry, chemical engineering, materials science, or a related field)
• At least 5 years professional experience (of which 3+ in a non-academic setting) in software development, designing and developing well-maintained software systems and collaborating with domain experts to design solutions that meet their needs
• Strong Python proficiency including experience with numeric and performance libraries (e.g. Numpy, Pytorch)
• Experience with relevant development tools and environments (e.g., git, Unix/Linux, cloud-based platforms, containerization) 
• Ability to balance rapid software delivery with software quality
• Ability to devise, communicate internally and own technical roadmaps, in a self-directed environment 
• Desire to work in a fast-paced team with diverse professional experiences and viewpoints

 Nice to Haves

• Experience developing software for scientific applications
• Familiarity with open source scientific libraries such as ASE, FairChem, Scikit-learn
• Experience building agentic AI solutions, including designing, developing, and implementing autonomous agents (e.g. Langchain and Langgraph)
• Experience with workflow management platforms (e.g. Apache Airflow)
• Experience with modern deep learning architectures
• Experience with the material d