C

Castelion

Designs and manufactures hypersonic strike weapons

Cloud Compute Engineer

Platform EngineeringConfirmed live in the last 24 hours
Full-timeAllen, TX, USANo salary listedIn-person

About the Job

Requirements

  • Experience building and operating distributed compute platforms used by multiple engineering teams.
  • Strong Python skills, including profiling, concurrency, memory management, and performance optimization.
  • Production experience with Ray and Kubernetes.
  • Experience designing batch-processing, event-driven, and user-submitted job systems.
  • Experience with Azure compute, storage, networking, identity, and monitoring services.
  • Demonstrated ability to optimize application code and data pipelines for performance, reliability, and cost.
  • Experience implementing observability, automated job recovery, and reproducible processing workflows.
  • Ability to build simple developer interfaces and work directly with users to automate complex workflows.

Responsibilities

  • Develop and operate distributed compute infrastructure supporting batch processing, custom jobs, simulation, calibration, preprocessing, and machine learning training.
  • Build event-driven workflows that automatically process newly ingested data, including flight-test and chamber calibration data.
  • Enable scalable machine learning training, Foxglove RDL preprocessing, data preparation, replay, and other user-submitted jobs.
  • Enable simulation and regression tests to run automatically in continuous integration and continuous delivery pipelines, expanding test coverage beyond standard runner limitations.
  • Profile and improve Python workloads, data flows, memory usage, concurrency, and resource utilization, as well as the underlying infrastructure.
  • Provide simple interfaces, application programming interfaces, or software development kits for engineers to submit, monitor, debug, and rerun jobs without managing infrastructure manually.
  • Implement logging, metrics, alerting, job traceability, and cost monitoring to make failures easy to diagnose and recover from.
  • Track code versions, inputs, configurations, and outputs so compute jobs can be reliably reproduced and audited.
  • Design efficient approaches to storage, data transfer, caching, partitioning, and preprocessing.
  • Work directly with engineers to understand their workflows and establish consistent compute patterns across unclassified and classified networks.

Desired Qualifications

  • Strong PyTorch experience, including distributed training, data loading, checkpointing, and graphics processing unit utilization.
  • Experience scaling machine learning training across large datasets and distributed compute resources.
  • Experience integrating simulation and regression workloads into continuous integration and continuous delivery pipelines.
  • Familiarity with large-scale engineering datasets, flight-test data, calibration, or scientific computing workflows.
  • Experience building compute platforms that support both classified and unclassified environments.
  • Experience improving processing throughput and turnaround time through workload optimization and infrastructure scaling.

About the Company

Castelion

Designs and manufactures hypersonic strike weapons

Castelion designs, tests, and manufactures hypersonic strike weapons for the U.S. military, aiming to deter future wars with fast, credible, non-nuclear deterrence. Its flagship Blackbeard is a low-cost, mass-producible hypersonic missile compatible with HIMARS/MLRS, built in-house with solid rocket motors, propellant, and a real-time, hardware-isolated flight computer. The company uses vertical integration and a rapid test-and-iterate cycle, with frequent flight tests and Project Ranger, a 1,000-acre facility in New Mexico to scale production. It competes with traditional defense primes on speed and cost, selling under government contracts and development awards to field advanced weapons at scale.

Company size
201-500
Company stage
Series C
Total funding
$1.5B
Headquarters
Torrance, CA
Founded
2022

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