3 days ago
Base Salary
$200k - $300k/yr
Responsibilities
- Build experiment-tracking and model-registry services, integrating tools such as MLflow where appropriate.
- Connect dataset, code, and configuration versions to training runs, checkpoints, and model versions.
- Develop APIs and adapters connecting training jobs, data services, and artifact storage.
- Implement reliable state handling, retries, diagnostics, and recovery for interrupted or failed workflows.
- Make checkpoints, model artifacts, and evaluation results easy to find and retrieve.
- Work directly with machine-learning engineers to simplify workflows and reduce manual record keeping.
- Deliver tested, observable services with compatible upgrades across cloud and customer-managed environments.
Requirements
- Production backend experience building 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 workflow solutions.
- Preferred experience with MLflow, Weights & Biases, model registries, or comparable experiment-management tools.
- Preferred experience integrating Kubernetes jobs, object storage, or machine-learning workflow systems.
- Preferred experience with reproducibility, data provenance, evaluation records, open-source software, on-premises deployments, or air-gapped deployments.
Benefits
- Full-time regular employee offer package includes bonus, benefits, and equity in addition to listed pay.
- Offers are contingent on a cleared background and possible reference check.
- The role is a full-time regular employee position; temporary employee benefits are available after 60 days where applicable.
Tech Stack
Categories
About Shield AI
Shield AI builds autonomous systems for military and national security customers, combining its Hivemind autonomy software with V-BAT and X-BAT unmanned aircraft and Aechelon simulation technologies. The privately held company sells hardware, software, and related services to U.S. and allied defense agencies. Founded in 2015 and headquartered in San Diego, it operates across the U.S., Europe, the Middle East, and Asia-Pacific, and its technology is used in operational deployments.