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Shield AI

Builds autonomous aircraft for defense

Staff Software Engineer ML Platform

Backend EngineeringPosted on Nov 9
Full-timeSan Diego, CA, USANo salary listedIn-person

About the Job

Requirements

  • Experience building production backend services for machine-learning platforms or data-intensive workflows.
  • Strong software engineering skills in Python or a comparable backend language.
  • Experience designing APIs, metadata models and persistent state for services used by other engineers.
  • Experience handling storage, partial failures, retries and consistency in distributed systems.
  • Understanding of training runs, checkpoints and model versioning.
  • Ability to work directly with machine-learning users and deliver maintainable software that solves their workflow problems.

Responsibilities

  • Build experiment-tracking and model-registry services, integrating tools such as MLflow where appropriate.
  • Connect exact dataset, code and configuration versions to training runs, checkpoints and model versions.
  • Develop APIs and adapters that connect training jobs, data services and artifact storage.
  • Make interrupted or failed workflows recoverable through reliable state handling, retries and useful diagnostics.
  • Make checkpoints, model artifacts and evaluation results easy to find and retrieve for further training, evaluation or deployment.
  • Work directly with machine-learning engineers to simplify their workflows and reduce manual record keeping.
  • Deliver tested services with observability and compatible upgrades across supported cloud and customer-managed environments.
  • Build the reference architecture used internally by engineering teams and delivered to customers building their own AI capabilities.

Desired Qualifications

  • Experience with MLflow, Weights & Biases, model registries or comparable experiment-management tools.
  • Experience integrating Kubernetes jobs, object storage or machine-learning workflow systems.
  • Experience with reproducibility, data provenance or evaluation records.
  • Experience supporting open-source software or on-premises and air-gapped deployments.

About the Company

Shield AI

Builds autonomous aircraft for defense

Shield AI builds autonomous aircraft and flight software for military and allied defense customers, with a focus on operations where conventional remote control breaks down. Its Hivemind AI pilot handles decisions during a mission, while the V-BAT aircraft gathers intelligence and locates targets. Aircraft makers use its software tools to develop and test their own autonomy, and its Aechelon business supplies visual and sensor simulation for pilot training. The company earns money from aircraft sales, autonomy software and contracted engineering and operational services. Shield AI was founded in 2015 and is headquartered in San Diego, California.

Company size
1,001-5,000
Company stage
Debt Financing
Total funding
$4.8B
Headquarters
San Diego, CA
Founded
2015

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