SandboxAQ
Scientific Software Engineer, ChemSim
Job Summary
SandboxAQ is seeking a Scientific Software Engineer to develop and maintain AI-accelerated computational chemistry tools for materials discovery. The role involves collaborating with domain experts to create scalable scientific software that leverages machine learning, generative AI, and high-performance computing. Key responsibilities include maintaining existing packages, designing new software, and ensuring stability and efficiency through testing and cloud integrations. Candidates should have strong Python skills, experience in scientific software development, and familiarity with relevant AI and computational tools.
Required Skills
Benefits
Job Description
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 discovery and material development processes
The US base salary range for this full-time position is expected to be $154K - $256K per year. Our salary ranges are determined by role and level. Within the range, individual pay is determined by factors including job-related skills, experience, and relevant education or training. This role may be eligible for annual discretionary bonuses and equity.
SandboxAQ welcomes all.
SandboxAQ
SandboxAQ leverages the compound effects of AI and advanced computing to address some of the biggest challenges impacting society. SandboxAQ technologies include AI simulation, cryptography management for cybersecurity, and AI sensing for global organizations.
See more jobsSafe Remote Job Search Tips
Verify Employer Thoroughly
Research the company's identity thoroughly before applying. Check for a professional website with contacts, active social media, and LinkedIn profiles. Verify details across platforms and look for reviews on Glassdoor or Trustpilot to confirm legitimacy.
Never Pay to Get a Job
Legitimate employers never require payment for applications, training, background checks, or equipment. Always reject upfront payment requests or demands for bank details, even if they claim it's for purchasing necessary work gear on your behalf.
Safeguard Your Personal Information
Protect sensitive data like SSN, bank details, or ID copies. Share this only after accepting a formal, written job offer. Ensure it's submitted via a secure company system or portal, never through insecure channels like standard email attachments.
Scrutinize Communication & Interviews
Watch for communication red flags: poor grammar, generic emails (@gmail), vague details, or undue pressure. Be highly suspicious of interviews held only via text or chat apps; legitimate companies typically use video or phone calls.
Beware of Unrealistic Offers
If an offer's salary or benefits seem unrealistically high for the work involved, be cautious. Research standard pay for similar roles. Offers that appear 'too good to be true' are often scams designed to lure you into providing information or payment.
Insist on a Formal Contract
Always secure and review a formal, written job offer or employment contract before starting work or sharing final personal details. Ensure it clearly defines your role, compensation, key terms, and conditions to avoid misunderstandings or scams.