Senior Software Engineer - Transport Infrastructure

Atoms•San Francisco, CA

15h•$200,000 - $235,000•Onsite

About The Position

Atoms is hiring a Senior Software Engineer for its Transport Infrastructure team. The role builds and operates infrastructure that supports autonomous systems and vehicle fleets, including developer tools, APIs, cloud and GPU compute, networking, and observability. The engineer will help connect the Transport domain to Atoms’ centralized infrastructure stack and enable teams to deploy, test, and iterate on vehicle hardware and simulation environments. The position is based onsite five days a week at Atoms’ San Francisco office. The base salary range is $200,000–$235,000 per year, with potential eligibility for equity awards. Atoms describes its work as building Physical AI and robots for industries including food, mining, and transport.

Requirements

Bachelor’s degree in Computer Science, Computer Engineering, or a related technical field, or equivalent practical experience.
At least 3 years of professional software engineering experience designing, building, and operating high-concurrency backend distributed systems in production.
Experience with languages such as Go, C++, Rust, or Python.
Hands-on experience with cloud infrastructure such as AWS, GCP, or Azure, and with containerization and orchestration tools such as Kubernetes and Docker.
Practical understanding of networking protocols such as TCP/IP, gRPC, WebSockets, and MQTT; load balancing; and edge-to-cloud or data center communications.
Experience managing compute orchestration, high-throughput storage pipelines, or GPU workloads for AI/ML training and simulation.
Broad system design skills and an infrastructure generalist mindset, with comfort working across networking, developer tooling, and compute clusters as priorities change.

Nice To Haves

Hands-on experience with hardware.

Responsibilities

Build developer experience tooling, APIs, and workflows that enable autonomous systems engineers to deploy, test, and iterate on vehicle hardware and simulation environments.
Architect and operate high-throughput GPU clusters for deep learning model training, fleet simulation, and large-scale data ingestion.
Design resilient, low-latency networking solutions for communication between autonomous vehicles in the field and distributed cloud data centers.
Develop scalable telemetry, logging, metrics, and tracing infrastructure to monitor vehicle fleet and cloud service health, performance, and safety in real time.
Build abstractions and proxy interfaces connecting the Transport domain with Atoms’ centralized infrastructure stack.