Member of Technical Staff — Product Engineering

The role

You will own the path from trained model to customer value. This includes building production systems for predictions, product surfaces, and demos that turn research into a product.

What you will do

• Build and operate production systems that deliver model predictions to customers
• Own reliability end to end including cost efficiency, monitoring, alerting, and incident response
• Design and build backend APIs, data delivery, integration patterns, and frontend dashboards
• Own packaging, security, observability, and upgrade machinery for deployment
• Deploy product into cloud, VPC, on-prem, and restricted networks
• Create product demos and prototypes with and for prospective customers
• Work directly in customer environments to integrate with data and systems
• Translate customer learnings into requirements for research and product
• Design tooling and playbooks to generalize solutions for customers

Required qualifications

• Strong generalist software engineering skills across the stack: backend systems, APIs, cloud infrastructure (GCP, AWS, or Azure), and modern frontend frameworks
• Experience deploying and operating ML systems in production
• Familiarity with containerization, orchestration, and infrastructure-as-code (e.g. Kubernetes, Docker, Terraform)
• Comfort working directly with customers: scoping ambiguous problems, building demos under time pressure, and representing the company technically
• Background in scalable model serving & deployment architectures and the systems around them
• Owns deliverables end-to-end, from requirements through autonomous execution

About the company

Causal is building a Large Physics foundation Model (LPM) to achieve general causal intelligence. The founding team has built and deployed AI in robotics, drug discovery, and particle physics at institutions like DeepMind, Waymo, Cruise, Insitro, Nabla Bio, and CERN.