Atomic is automating tool and die making, a critical bottleneck in how goods are manufactured. Our mission is to transform the tribal knowledge of tool and die makers into software that powers new systems which are orders of magnitude more productive.

Infrastructure Engineer (SRE)

Department: Engineering – Infrastructure

About Atomic Industries

Atomic Industries is reinventing how the world makes things. From cars and aerospace systems to medical devices and packaging, most physical goods begin life in a mold or are shaped by a manufacturing tool. Producing these tools has always been slow, manual, and dependent on scarce expertise, taking weeks or months. We’re changing that.

At our Detroit headquarters, we combine the industrial DNA of America’s manufacturing heartland with the speed, intelligence, and precision of Silicon Valley. Our AI-driven platform tackles the hardest problems in geometry, process planning, and fabrication, collapsing production timelines from months to days and soon, minutes. We don’t just build software; we run a fully operational factory where our technology produces production-grade tooling every week, enabling tight feedback loops and rapid iteration.

Backed by top-tier investors, we’re restoring speed, flexibility, and capability to the American industrial base. Our mission is to make manufacturing as agile and scalable as the digital world, and in doing so, rebuild the infrastructure of the physical economy.

About the Role

As an Infrastructure Engineer at Atomic, you’ll own the systems that power high-performance simulation, geometry processing, and factory automation. You’ll be responsible for building and maintaining the hybrid infrastructure that spans cloud, on-prem, and GPU compute environments.

This role is ideal for engineers who thrive at the intersection of reliability, performance, and engineering velocity.

What You’ll Do

• Manage and improve CI/CD pipelines (GitHub Actions, Terraform, HashiCorp stack)

• Orchestrate compute workloads across cloud and bare-metal GPU clusters

• Design systems for secure, fault-tolerant deployment and observability

• Build internal tooling to accelerate developer workflows and operations

• Partner with engineers on simulation, ML, and backend teams to scale infrastructure

• Monitor and tune system performance under high computational loads

What We’re Looking For

Minimum Qualifications

• 5+ years in DevOps, infrastructure, or site reliability engineering

• Proficiency with container orchestration (Nomad, Kubernetes), IaaC, and Linux

• Strong scripting and programming skills (Python, Bash, Go)

• Experience with hybrid (cloud + on-prem) infrastructure

• Familiarity with distributed systems, caching layers, and observability tools

Bonus Points

• Background supporting ML, simulation, or HPC workloads

• Experience managing large GPU fleets or multi-node compute tasks

• Security or compliance experience (ITAR, SOC2, CMMC)

• Track record of building tooling for high-autonomy engineering teams

How We Work

• Fast iteration: We deploy code daily and validate it in the factory every week

• Factory-first mindset: Engineers spend time on the shop floor to understand the real-world impact of their work

• Low ceremony, high ownership: We value well-written design docs, tested code, and real results — not meetings

• Collaborative culture: Geometry, AI, and robotics teams are tightly integrated and co-develop the product together

Benefits

• Competitive salary and generous equity package

• Full medical, dental, and vision coverage for employees and dependents

• 401(k)

• PTO with a 15-day minimum

• Quarterly team travel to Detroit

• Visa support for TN, E‑3, and O‑1 candidates

• Hardware stipend and on-site prototype lab access

Atomic currently offers a challenging environment for engineers from computational geometry/meshing, CFD, to physical HPC + ML problems. We're excited to break down barriers of traditional physics solvers using deep learning and other advanced methodologies. We're highly focused on a single application and value chain, so we're not recreating the wheel in terms of making broad platforms for users. We're actually doing the opposite, creating a computational API that places humans in the back seat. You'll be working on problems that fundamentally move the field of human creativity and design forward.