Senior Machine Learning Engineer (AI)

Location: Remote in the United States

Base salary: $211,000–$249,000 annually, plus equity in the form of stock options.

Company

hirify.global develops NodeZero, a cybersecurity platform for autonomous penetration testing and security assessment operations.

What you will do

• Build and own training and post-training pipelines, including data preparation, fine-tuning, preference optimization, experiment tracking, artifact management, and reproducibility.
• Develop production inference and model-serving infrastructure with provider routing, fallback, regional data-residency controls, batching, and caching.
• Own model release workflows with versioned deployable configurations, shadow and canary deployments, tenant-level rollout, and rapid rollback.
• Build model-layer monitoring for behavioral drift, regressions, output quality, latency, token usage, and cost budgets.
• Develop retrieval, embedding, ETL, and GraphQL pipelines that connect model outputs, run history, and evaluation results to products and internal tools.
• Partner with AI researchers, backend engineers, and infrastructure engineers to move prototypes into production and feed operational findings back into research.

Requirements

• 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.
• Experience taking ML or LLM-backed systems from prototype to production and operating them.
• Hands-on experience with ML pipelines, training or fine-tuning workflows, experiment tracking, model registries, and reproducible data preparation.
• Experience with production model-serving infrastructure, cloud platforms such as AWS, Azure, or GCP, Docker, Kubernetes, SQL, and production data pipelines.

Nice to have

• Experience with agentic systems, supervised fine-tuning, distillation, preference optimization, or reinforcement learning infrastructure.
• Experience with model gateways, multi-provider routing, self-hosted or customer-hosted inference, GPU infrastructure, quantization, or inference optimization.
• Experience with PostgreSQL, Neo4j, GraphQL, Datadog, Prometheus, Grafana, and distributed tracing across model calls.
• Experience shipping ML into regulated, air-gapped, or customer-controlled environments, including FedRAMP-compliant environments.

Culture & Benefits

• Remote work for this role, with a broader mix of remote and hybrid arrangements across the company.
• Health, vision, and dental insurance for employees and families.
• Flexible vacation policy and generous parental leave.
• Full-time employees receive equity in the form of stock options.
• Inclusive, collaborative environment focused on ownership, respect, learning, and results.