5-7 years of production ML engineering experience.
Strong proficiency in modern Python; familiarity with Rust (PyO3) is a plus.
Experience with distributed training using TensorFlow or PyTorch.
Knowledge of Kubernetes and workflow orchestration tools (Flyte, Airflow, Dagster).
Familiarity with experiment tracking tools like Weights & Biases or MLflow is a nice-to-have.
Responsibilities
Build and maintain training and dataset infrastructure for autonomous perception systems.
Enhance tools and SDKs utilized by perception engineers.
Utilize frontier models for data curation, labeling, and synthetic data generation.
Monitor training jobs, evaluations, and model versions.
Collaborate with engineering teams across various business lines.
Benefits
Equity options available.
Opportunity to work on cutting-edge defense technology.
Collaborative environment with cross-functional teams.
Direct impact on the development of autonomous systems.
Full Job Description
Type: Direct hire, full-time • Base: $166,000-$220,000 + equity • Clearance: U.S. Person required; Top Secret eligibility desirable
VDS is recruiting an ML infrastructure engineer to build the training and data platform behind autonomous perception systems used across a defense-technology company.
What you'll do
Build and run training and dataset infrastructure, including multi-sensor data indexing.
Improve tools and SDKs used by perception engineers.
Use frontier models for data curation, labeling, synthetic data and search.
Track training jobs, evaluations and model versions.
Partner with engineering teams in each business line.
What you bring
Strong modern Python; some Rust (PyO3) is a plus.
Distributed training in TensorFlow or PyTorch.
Kubernetes and workflow orchestration (Flyte, Airflow or Dagster).
Nice to have
Experiment tracking with Weights & Biases or MLflow.
Senior Machine Learning Engineer, Core Development (Verify)
Type: Direct hire, full-time • Base: [confirm range] + equity • Clearance: [confirm; U.S. Person likely]
VDS is recruiting a senior ML engineer to build core machine-learning capabilities shared across a defense-technology company's autonomy products.
What you'll do
Develop and ship models used across multiple product lines.
Build reusable ML components, pipelines and evaluation tools.
Work with autonomy, perception and platform teams.
What you bring
[confirm years] years of production ML engineering.
Python and PyTorch or TensorFlow; experience deploying models at scale.
