Build core product and infrastructure, ship end-to-end features across the stack, develop data ingestion and multimodal representation systems, implement LLM-based agentic systems and other AI approaches, and act as a technical leader mentoring engineers while defining technical vision and culture.
We’re building the scientific intelligence platform for the physical world, to accelerate breakthroughs in semiconductors, batteries, advanced materials, aerospace, and beyond. These industries represent trillions in spend, but are still trapped in outdated software. We’re changing that by building the intelligence layer to help scientists and engineers move faster and solve core problems -- R&D through manufacturing.
We have a once-in-a-generation opportunity to create a category-defining company at the intersection of AI and the physical sciences. And we’re building a world-class team to do it.
We recently raised a seed round led by Greylock, with participation from Neo, BoxGroup, Liquid 2, and top angels including Jeff Dean + leadership at OpenAI and AMD. Our team (ex-Applied Intuition, SpaceX, Warp, Jane Street, Microsoft) works in-person in San Francisco. Our office is located walking distance from 4th and King Caltrain station.
What you’ll do:
- Architect and build the early foundations of Altara’s core product and infrastructure.
- Ship end-to-end features across the stack, balancing speed, scope, and user experience.
- Develop data ingestion and representation systems that can automatically extract structure and insight from multimodal, messy real-world scientific data (e.g., R&D databases, spreadsheets, images, technical documents, etc).
- Build both LLM-based agentic systems and implementations beyond LLMs.
- Act as a technical leader across the organization, mentoring top talent and helping define Altara’s technical vision and engineering culture as we scale.
We would love to meet you if you:
- Care about solving meaningful scientific challenges and disrupting the industry, not just building another SaaS tool.
- Have shipped 0-to-1 products at a startup, applied AI lab, or other high-growth environments before.
- Consider yourself a product-first engineer - you start from the user problem, not the technology, and make smart technical tradeoffs to deliver impact fast.
- Love to learn, bias toward action, and enjoy taking full ownership of problems end-to-end.
- Thrive in fast-paced, unstructured environments with evolving requirements.
- Already use AI tools daily and think critically about how to push their limits.
Bonus points if you have:
- Worked at an early stage startup, founded a company, or plan to start one someday.
- Applied AI/ML engineering and research experience, especially with building search and ranking tools, LLM-based applications, agentic workflows, and computer vision.
- Experience or deep curiosity in science.
Learn More about Altara
- Video
- Blog post
- TechCrunch
- Follow us on LinkedIn and X
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