jobapplier

Senior Machine Learning Engineer (Autonomous Defense)

Horizon3

Skills

Required

  • GPU infrastructure / quantization / inference
  • optimization
  • ML / LLM-backed
  • SQL
  • production data pipelines
  • AWS
  • Azure
  • Docker
  • Kubernetes
  • Python
  • PostgreSQL
  • Neo4j
  • Prometheus

Preferred

  • training
  • tooling
  • LLM / agentic systems
  • post-training
  • ML pipelines
  • fine-tuning workflows
  • experiment tracking
  • artifact and model registries
  • data preparation

Join NodeZero as a Senior Machine Learning Engineer on the Defensive Agent team. You will be responsible for taking our defensive models from research to production, building and owning the training and post-training pipelines, inference and serving layer, release path for model-layer artifacts, and monitoring for the model layer. You will work closely with AI researchers and backend/infrastructure engineers, and have a direct impact on the success of our AI products. Enjoy a flexible work environment, growth opportunities, and an inclusive and diverse team culture.

Responsibilities

  • Construire et posséder les pipelines d'entraînement et de post-entraînement, y compris la préparation des données, l'optimisation des préférences et le suivi des expériences.
  • Développer l'infrastructure d'inférence et de service, y compris la passerelle de modèle avec le routage des fournisseurs et le basculement.
  • Construire la surveillance pour la couche de modèle, y compris la dérive comportementale, la détection des régressions et les signaux de qualité de sortie.

Requirements

  • Solid proficiency in SQL and experience with production data pipelines
  • Experience building applications on cloud computing platforms such as AWS, Azure, GCP, using container technologies such as Docker and Kubernetes
  • Experience building and operating inference or model-serving infrastructure in production, including latency and cost optimization
  • Demonstrated experience taking ML or LLM-backed systems from prototype to production and operating them
  • 5+ yrs professional software engineering experience, with strong production Python
  • Bachelor's Degree in Computer Science, Computer Engineering or related field, or equivalent practical experience
  • Experience with GPU infrastructure, quantization, or inference optimization
  • Experience with database architectures including relational (PostgreSQL) and graph (Neo4j), and with GraphQL backends
  • Experience with observability tooling (Datadog, Prometheus, Grafana) and distributed tracing, including tracing across model calls

Preferred

  • Hands-on experience with ML pipelines and tooling: training or fine-tuning workflows, experiment tracking, artifact and model registries, and reproducible data preparation

Experience operationalizing LLM or agentic systems specifically

  • Hands-on post-training experience: supervised fine-tuning, distillation, preference optimization, or RL, including the infrastructure around the runs
  • Experience with model gateways or multi-provider routing, and with self-hosted or customer-hosted inference (vLLM, TGI, Bedrock, or similar)
  • Experience shipping ML into regulated, air-gapped, or customer-controlled environments, or under compliance regimes like FedRAMP

Pay

USD 211,000 - 249,000