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# Software Engineer - Transport Infrastructure

- **Company:** ATOM, INC.
- **Location:** San Francisco, CA, United States
- **Experience:** Expert
- **Salary:** $200,000.0 - $235,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Big Data, C++ (Programming Language), Cloud Computing, Computer Clusters, Computer Engineering, Data Centers, Data Transmissions, Programming Tools, Distributed Systems, Python (Programming Language), Machine Learning, Message Queuing Telemetry Transport (MQTT), Network Protocols, Cloud Services, Software Engineering, TCP/IP, WebSocket, Workflow Management Systems, Data Logging, Load Balancing, Deep Learning, Containerization, Kubernetes, Information Technology, Grpc, Docker
- **Published:** October 26, 2026
- **Apply:** https://startup.jobs/senior-software-engineer-transport-infrastructure-atoms-10559902

## About the Role

* Bachelor's degree in Computer Science, Computer Engineering, or a related technical field (or equivalent practical experience).
 * 3+ years of professional software engineering experience designing, building, and operating high-concurrency backend distributed systems in production using languages like Go, C++, Rust, or Python.
 * Hands-on experience with cloud infrastructure (AWS, GCP, or Azure), containerization, and orchestration tools like Kubernetes and Docker.
 * Practical understanding of networking protocols (TCP/IP, gRPC, WebSockets, 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, comfortable jumping between networking, developer tooling, and compute clusters as priorities evolve.
 * Hands-on experience with hardware is a strong plus.

## Description

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