Senior Machine Learning Engineer, Autonomous Defense
Horizon3 · Remote · US, Remote ·
COMPENSATION
€•• – ••k
Listed on the employer's job board (Ashby)
- Senior ML Engineer
- Remote / Hybrid (US)
- Python + Kubernetes
- LLM Ops focus
- $211k-$249k base
Join the Autonomous Defense team at Horizon3 to bridge the gap between AI research and production. You will build the pipelines, serving infrastructure, and release machinery that allow NodeZero’s agents to operate securely across thousands of customer tenants.
This position requires owning the path from model to production, ensuring reproducibility, low latency, and cost efficiency. You will collaborate closely with researchers and backend engineers to deploy robust defensive capabilities.
What you'll do
- Build and own training pipelines including data prep, fine-tuning, and experiment tracking.
- Develop inference serving layers with provider routing, batching, and caching.
- Manage model release paths with versioned configs, canary deployments, and rollbacks.
- Implement monitoring for behavioral drift, regression, latency, and cost accounting.
- Construct data pipelines for retrieval and embedding with strict tenant isolation.
- Optimize inference cost and latency to support data-driven product decisions.
- Develop ETL and GraphQL features to integrate model outputs into the product.
- Partner with researchers to transition prototypes into production environments.
What you'll need
- Bachelor's in Computer Science or equivalent practical experience.
- 5+ years of software engineering experience with strong production Python skills.
- Proven track record of taking ML or LLM systems from prototype to production.
- Hands-on experience with ML pipelines, artifact registries, and reproducible data prep.
- Experience operating inference infrastructure with a focus on latency and cost.
- Proficiency with cloud platforms like AWS, Azure, or GCP using Docker and Kubernetes.
- Solid SQL skills and experience building production data pipelines.
Nice to have
- Experience operationalizing LLM or agentic systems specifically.
- Hands-on post-training work such as SFT, distillation, or preference optimization.
- Familiarity with model gateways, multi-provider routing, or self-hosted inference.
- Experience with GPU infrastructure, quantization, or inference optimization.
- Knowledge of PostgreSQL, Neo4j, and GraphQL backends.
- Proficiency with observability tools like Datadog, Prometheus, or Grafana.
- Experience shipping ML solutions in regulated or air-gapped environments.
Stack
- Python
- SQL
- Docker
- Kubernetes
- AWS
- Azure
- GCP
- GraphQL
- PostgreSQL
- Neo4j
- Datadog
- Prometheus
- Grafana
- vLLM
- TGI
- Bedrock
How you'll work
- Remote and hybrid work models available depending on location.
- Some roles may require regular presence at the Chicago office.
- Global team with a culture of respect and collaboration.
What you get
- Competitive base salary range of $211,000 to $249,000 annually.
- Equity package in the form of stock options for full-time roles.
- Health, vision, and dental insurance for employees and families.
- Flexible vacation policy and generous parental leave.
- Inclusive culture with diverse career development opportunities.