Engineering Intern
Veriqa is the quality intelligence layer for regulated industries, starting with pharma. We ingest the fragmented, unstructured quality data manufacturers already generate — batch records, deviations, CAPAs, vendor COAs, handwritten and paper files — into one connected graph, and surface the patterns no human or legacy system can see. Our team comes from AWS, Berkeley, UC San Diego, Miltenyi Biotec, and multi-generational pharma manufacturing. We’re building the system every drug on earth depends on.
The Role
You’ll build AI systems in a domain where being wrong isn’t an option. Pharma quality is regulated, high-stakes, and allergic to hallucination — which makes the engineering hard: deterministic pipelines, source-traceable outputs, fine-tuned OCR on messy handwritten records, a knowledge graph over fragmented data, and multi-agent orchestration with a human in the loop at every gate.
Your work spans the full stack — backend, ML and OCR, data ingestion, eval and observability, and the interfaces quality teams work in. You’ll ship to real customers on real data, own features end to end, and shape core architecture from day one.
About the Role
- Internship timing flexible to your availability (winter, spring, summer)
- Based in San Francisco, on-site
- Flexible working hours
- Work directly with the founders and early customers
- Opportunity to convert to full-time for strong performers
What Makes You a Good Fit
- Comfortable across the stack (e.g. Python, TypeScript/Next.js, modern cloud and GPU infra)
- Experience building production systems with real users
- Strong intuition for product, UX, and system design
- Relentless builder with a bias toward shipping
- Learn new technologies fast and own entire features end to end
Bonus Points
- Experience with LLMs, multi-agent systems, RAG, or knowledge graphs
- Worked with OCR, computer vision, or model fine-tuning
- Comfortable with large, messy, or unstructured datasets
- Interest in regulated industries, healthcare, or life sciences
If you want to build AI the world can trust where it matters most, come join us.