Senior Machine Learning Engineer, Autonomous Defense

The role

You will get defensive models into production and maintain them. You will build training pipelines, serving infrastructure, and release machinery to turn research into capabilities running against customer tenants.

What you will do

• Build and own training and post-training pipelines
• Build the inference and serving layer
• Own the release path for model-layer artifacts
• Build monitoring for the model layer
• Build data and context pipelines that feed inference
• Optimize cost and latency across the inference path
• Develop core product features in ETL and GraphQL
• Partner with researchers to move prototypes into production

Required qualifications

• Bachelor's Degree in Computer Science, Computer Engineering or related field, or equivalent practical experience
• 5+ yrs professional software engineering experience, with strong production Python
• Demonstrated experience taking ML or LLM-backed systems from prototype to production and operating them
• Hands-on experience with ML pipelines and tooling: training or fine-tuning workflows, experiment tracking, artifact and model registries, and reproducible data preparation
• Experience building and operating inference or model-serving infrastructure in production, including latency and cost optimization
• Experience building applications on cloud computing platforms such as AWS, Azure, GCP, using container technologies such as Docker and Kubernetes
• Solid proficiency in SQL and experience with production data pipelines

Nice to have

• 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 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
• Experience shipping ML into regulated, air-gapped, or customer-controlled environments, or under compliance regimes like FedRAMP

Benefits

• Equity package in the form of stock options
• Health, vision & dental insurance for you and your family
• Flexible vacation policy
• Generous parental leave

About the company

Horizon3 is a fast-growing, remote cybersecurity company dedicated to the mission of enabling organizations to proactively find and fix and verify exploitable attack vectors before criminals exploit them.