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Member of Technical Staff — Product Engineering

Causal Labs· Infrastructure
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San Francisco, SingaporeFull-timePosted 2mo ago

About the role

Software engineer focused on building and operating production systems for real-time model predictions, delivering customer-ready surfaces, and enabling end-to-end deployment of physics-based AI products.

Responsibilities

  • Build and operate the production systems that deliver model predictions to customers around hard real-time deadlines — owning reliability end to end, from cost efficiency to monitoring, alerting, and incident response
  • Design and build the full product surface: backend APIs and data delivery, integration patterns, and frontend dashboards and visualizations that make predictions actionable
  • Own the packaging, security, observability, and upgrade machinery to deploy our product into customer environments — cloud, VPC, on-prem, and restricted networks
  • Create product demos and prototypes with and for prospective customers, iterating rapidly alongside go-to-market
  • Work directly in customer environments when needed: integrate with their data and systems, ship solutions on-site, and translate what you learn into requirements for research and product
  • Design the tooling and playbooks that let solutions built for one customer generalize to the next

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, ideally across diverse or customer-controlled environments
  • 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

Skills

Required:Software engineering across the stackProduction ML systemsContainerization and orchestration

Benefits

  • [Benefits not specified in the description]
Last updated Oct 2, 2026. Interested? Apply on the company site.

About Causal Labs

Towards general causal intelligence

Causal Labs is building a Large Physics foundation Model (LPM) to learn causality through physics and weather

causalityphysicsweatherAIfoundation model
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