Physical Superintelligence

AI systems, computational science, software engineering, physics

MemberofTechnicalStaff,Infrastructure

Boston, United States FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Mid candidates.

The Brief

“Member of Technical Staff, Infrastructure at Physical Superintelligence. Skills: Platform infrastructure, Cloud foundations, CI/CD pipelines, Production deployments, Multi-cloud infrastructure, Infrastructure-as-code, Release engineering, MLOps, Operational excellence. Own the full infrastructure stack end-to-end, from cloud foundations through CI/CD pipelines to production deployments. Build and operate multi-cloud infrastructure for our AI platform across GCP, AWS, and adjacent providers”

What You'll Achieve.

Discover and commercialize transformative physics breakthroughs at scale with artificial superintelligence, safely, verifiably, and for broad public benefit; Ship code from commit to production; Fast, safe deploys; Meet SLOs; Build systems that scale without bureaucracy

Industry & Context.

AI systems, computational science, software engineering, physics
Problems you'll solve

Systems thinking; Incident response; Reducing toil with code

Eligibility Requirements

In-person role, On-call

What They're Looking For.

Must Have

Four or more years operating cloud infrastructure in production at companies known for engineering rigor (e. g. , Stripe, Cloudflare, Datadog, Snowflake, Databricks, Google, Netflix, or comparable), at multi-cloud scale, Written code and shipped infrastructure that paying customers, internal teams, or large user bases depend on every day, Deep fluency with infrastructure as code (Terraform, Pulumi, or comparable), Deep fluency with CI/CD systems, Deep fluency with Kubernetes, Deep fluency with major cloud platforms (GCP and AWS at minimum), Built and operated multi-cloud production deployments end-to-end, from initial cloud setup through to release pipelines, Machine learning and training-workload operations experience, GPU scheduling, Distributed training infrastructure, Model-serving pipelines, Observability for ML systems, Run production training jobs and shipped served-model surfaces, Operational excellence and on-call discipline, Led incidents, Written runbooks, Reduced toil with code, Built systems that scale without bureaucracy, Favor self-service abstractions over tickets and visibility over heroics

Nice to Have

Built CI/CD or release engineering pipelines from scratch at a fast-growing company, Hands-on with model serving infrastructure such as vLLM, Triton, or comparable, Production observability with OpenTelemetry, Prometheus, Grafana, or comparable, Background in scientific computing, HPC, or research compute environments

What You'll Do.

Own the full infrastructure stack end-to-end

from cloud foundations through CI/CD pipelines to production deployments

Build and operate multi-cloud infrastructure for our AI platform across GCP

and adjacent providers

Establish the infrastructure-as-code discipline at PSI: choose the tooling

and make every research workflow

and customer-facing AI product deployable through code

Design and run the release engineering pipeline that ships code from commit to production

Operate the production infrastructure that powers our AI platform at scale: the paid API

model training jobs for our proprietary physics LLM

agentic research workflows

and customer deployments

build observability and alerting

schedule GPU and CPU capacity

lead incident response

Be the leverage layer for the rest of engineering

not tickets they wait on

How You'll Work.

Team & Collaboration

Platform engineers depend on you; Product engineers depend on you; Security engineers depend on you; Research engineers depend on you

Full Job Description

Overview Physical Superintelligence is a stealth startup with roots at Google, NVIDIA, Harvard, Meta, MIT, Oxford, Johns Hopkins, Cambridge, and the Perimeter Institute building AI systems to discover new physics at scale. We are seeking engineers to build platform infrastructure at the intersection of computational science, AI systems, and software engineering. Our mission is to discover and commercialize transformative physics breakthroughs at scale with artificial superintelligence, safely, verifiably, and for broad public benefit. The last century's golden age of physics gave us transistors, lasers, and nuclear energy. We believe artificial superintelligence will unlock the next one. We're creating the infrastructure to industrialize scientific discovery and usher in this new era. We have one product: new physics, at scale. Role and Responsibilities Own the full infrastructure stack end-to-end, from cloud foundations through CI/CD pipelines to production deployments. Build and operate multi-cloud infrastructure for our AI platform across GCP, AWS, and adjacent providers. Establish the infrastructure-as-code discipline at PSI: choose the tooling, design the modules, and make every research workflow, training job, and customer-facing AI product deployable through code. Design and run the release engineering pipeline that ships code from commit to production. Every change flows through automated tests, security scans, and progressive rollouts. Fast, safe deploys are the default; long manual release cycles are not. Operate the production infrastructure that powers our AI platform at scale: the paid API, model training jobs for our proprietary physics LLM, agentic research workflows, and customer deployments. Define and meet SLOs, build observability and alerting, schedule GPU and CPU capacity, lead incident response. Be the leverage layer for the rest of engineering. Platform, product, security, and research engineers all depend on you for reliable cloud primitives,

Free ATS check

Applying for this Member of Technical Staff, Infrastructure role?

Most applicants get filtered before a human reads their resume. See if yours makes the cut.

How to Apply on Ashby

  • Ashby is a fast modern ATS — most applications take under 3 minutes.
  • The resume parser is strong; verify parsed experience dates and job titles.
  • Custom screening questions are often scored algorithmically — answer completely.
  • Location field affects geo-based screening; use your actual metro area.

ANONYMOUS · UNFILTERED

What do employees actually say about Physical Superintelligence?

Real rants from real employees. Read before you apply.

Read Company Rants →