Backend Engineer (Python/Go) for AI-Driven Simulations

United States Digital Space LLC

London

Hybrid

NOK 1,141,000 - 1,648,000

Full time

9 days ago

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Benefits offered by this job

Equity options
10% employer pension contribution
Free office lunches
Flexible working
Hybrid setup

Job summary

United States Digital Space LLC is seeking passionate software engineers to join our AI-driven simulation platform, enabling data scientists, ML engineers and simulation engineers to create, train, and deploy physics-informed models. You’ll own features end-to-end, ensuring quality, scalability and observability from development to production.

Join a hybrid, UK-based team with a Shoreditch office and remote flexibility, and help shape the future of our software engineering practices while

Qualifications

  • Experience building platforms for data scientists and simulation engineers.
  • Strong collaborative and cross-functional teamwork skills.
  • Ownership from implementation to production, including testing and deployment.
  • Familiarity with event-driven messaging and containerised environments.

Responsibilities

  • Take part in building a platform used by Data Scientists and Simulation Engineers to build, train and deploy Deep Physics Models.
  • Work in a focused, stream-aligned, cross-functional team that makes its own implementation decisions to meet objectives.
  • Gather and leverage domain knowledge from Data Scientists and Simulation Engineers using the product.

Tools

Python
Go
Kubernetes
NATS
RabbitMQ
Kafka
CI/CD

Job description

United States Digital Space LLC is seeking passionate software engineers to join our AI-driven simulation platform, enabling data scientists, ML engineers and simulation engineers to create, train, and deploy physics-informed models. You’ll own features end-to-end, ensuring quality, scalability and observability from development to production.

Join a hybrid, UK-based team with a Shoreditch office and remote flexibility, and help shape the future of our software engineering practices while

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