Senior Machine Learning Engineer, Autonomous Defense

What you'll do

• Build and operate reproducible training, post-training, inference, and serving pipelines for ML models.
• Manage model releases, monitoring, evaluation, and rollback; optimize inference cost and latency.
• Build data, retrieval, and product pipelines that deliver model outputs and evaluation results.

What they ask for

• Bachelor's degree in Computer Science, Computer Engineering, or a related field, or equivalent practical experience.
• 5+ years of professional software engineering experience, with strong production Python.
• Demonstrated experience taking ML or LLM-backed systems from prototype to production and operating them.
• Experience with ML pipelines and tooling, production model-serving infrastructure, cloud platforms and containers, SQL, and production data pipelines.

Nice to have

• Experience operationalizing LLM or agentic systems and hands-on post-training workflows.
• Experience with model gateways, GPU or inference optimization, PostgreSQL, Neo4j, GraphQL, observability, or regulated and customer-controlled environments.

Pay

$211,000 - $249,000 annually (base salary)

Tools

Python, AWS, Azure, GCP, Docker, Kubernetes, SQL, GraphQL

AI focus

Productionize and operate defensive ML and LLM-backed systems, including training and post-training, model serving, evaluation, retrieval and embeddings, monitoring, and inference cost and latency optimization.