Cloud Compute Engineer

Description

The company builds advanced defense systems and is moving quickly at an early stage, where each hire has large ownership and can directly shape the product and the company's direction.

This role sits on the seeker team and centres on a shared compute platform for data processing, simulation, calibration and machine learning.

You would move compute-heavy work that now runs on individual laptops and ad hoc scripts onto a shared, automated and dependable platform used by several engineering teams.

The work is hands-on and spans data processing, ML training and test infrastructure, with a direct effect on engineering speed, data throughput and how far seeker development can scale.

Responsibilities

• Design and run a distributed compute platform for batch jobs, custom jobs, simulation, calibration, preprocessing and ML training.
• Build event-driven pipelines that process newly ingested data as it arrives, including flight-test and chamber calibration data.
• Make ML training, Foxglove RDL preprocessing, data preparation, replay and other user-submitted jobs scale.
• Connect simulation and regression tests to CI/CD so they run automatically and go beyond the limits of standard runners.
• Profile and tune Python code, data flows, memory use, concurrency and resource use, not only the infrastructure beneath them.
• Create simple interfaces, APIs or SDKs so engineers can submit, watch, debug and rerun jobs without managing infrastructure themselves.
• Add logging, metrics, alerts, job tracing and cost monitoring so failures are easy to find and recover from.
• Record code versions, inputs, configurations and outputs so any job can be reproduced and audited.
• Design storage, transfer, caching, partitioning and preprocessing approaches that handle large data volumes.
• Work with engineers day to day to learn their workflows and set shared compute patterns across unclassified and classified networks.

Requirements

• Have built and run distributed compute platforms that several engineering teams depend on.
• Write strong Python, including profiling, concurrency, memory management and performance tuning.
• Have used Ray and Kubernetes in production.
• Have designed batch, event-driven and user-submitted job systems.
• Have worked with Azure compute, storage, networking, identity and monitoring services.
• Have improved application code and data pipelines for speed, reliability and cost.
• Have added observability, automatic job recovery and reproducible processing workflows.
• Can build simple developer tools and work with users to automate complex processes.
• Preferred: Strong PyTorch skills, including distributed training, data loading, checkpointing and GPU utilization.
• Preferred: Experience scaling ML training over large datasets and distributed resources.
• Preferred: Experience putting simulation and regression workloads into CI/CD pipelines.
• Preferred: Familiarity with large engineering datasets, flight-test data, calibration or scientific computing.
• Preferred: Experience building platforms that serve both classified and unclassified environments.
• Preferred: Experience raising processing throughput and shortening turnaround through workload tuning and infrastructure scaling.

Conditions

The position may require access to classified information or restricted U.S. Government sites, systems or information, as set by the company and/or U.S. Government requirements. If so designated, your employment in the role may depend on obtaining and keeping the required U.S. Government security clearance or other government authorization, and on meeting any citizenship or other eligibility rules set by law, regulation, executive order or contract. You will be told if and when these apply.

The role requires access to export-controlled information, so employment or hiring a contractor depends on being able to access all applicable export-controlled information without additional export licensing from the Bureau of Industry and Security and/or the Directorate of Defense Trade Controls.

Benefits

• The company offers a generous benefits package; details are at the bottom of its Careers page.