MLO Engineer (Machine Learning Operations)

Location: Mojave, California, United States; onsite position with no travel required and a 9/80 schedule.

Base salary: $142,000–$165,000 per year.

Company

hirify.global develops reusable hypersonic flight-testing and aerospace technologies, including autonomous air-launched Talon-A vehicles for operationally realistic flight environments.

What you will do

• Design, deploy, and operate reliable infrastructure for ML, LLM, and RAG workloads, including AWS-based model operations and future AI compute requirements.
• Host, maintain, monitor, and optimize RAG systems and vector retrieval infrastructure such as Qdrant.
• Develop logging, observability, alerting, and production-support capabilities for system health, performance, cost, and reliability.
• Integrate COTS products, third-party services, open-source tools, and custom AI capabilities into production environments.
• Build APIs, plugins, SDKs, CLIs, and integrations for OpenWebUI, Hugging Face, Wilbur, internal applications, Streamlit services, and web infrastructure.
• Collaborate with software, data, infrastructure, security, and domain teams to evaluate AI technologies and deliver maintainable solutions.

Requirements

• Experience designing, deploying, and operating reliable, observable software or ML systems in production.
• Experience with ML workloads, cloud infrastructure, and model deployment, preferably in AWS.
• Experience with a programming language such as Python, Rust, C, MATLAB, or equivalent.
• Experience developing and integrating APIs, services, plugins, or other software interfaces.
• Experience with containerization, deployment, and orchestration technologies such as Docker, Kubernetes, or Dagster.
• Experience with logging, monitoring, troubleshooting, and production support.
• Comfort with CLI tools and shell scripting, including Bash or Windows batch scripting.
• Knowledge of DevSecOps and CI/CD systems such as Jenkins, GitLab, or Bamboo.
• Ability to evaluate technical options, integrate external or open-source software, and deliver practical solutions with stakeholders.
• BS in Computer Science, Engineering, Data Science, or a related field, or applicable experience in lieu of a degree; 5–10 years of professional experience in software engineering, cloud infrastructure, data engineering, MLOps, AI engineering, or a related discipline.

Nice to have

• MLOps experience hosting, maintaining, monitoring, and optimizing LLM and RAG systems.
• Experience running inference workloads in AWS services including EC2, Lambda, ECS, EKS, S3, and CloudWatch.
• Experience optimizing RAG systems, vector databases, and retrieval pipelines, including Qdrant.
• Familiarity with LLM APIs, embedding models, Hugging Face tools, OpenWebUI, and AI application frameworks.
• Experience developing reusable plugins, SDKs, CLIs, or developer platforms for multiple teams.
• Experience with frontend and backend integration, Streamlit, NGINX, reverse proxies, load balancing, or related web infrastructure.
• Experience evaluating AI systems for performance, latency, scalability, reliability, cost, and resource utilization.
• Familiarity with relational, non-relational, and vector databases such as PostgreSQL, MongoDB, and Qdrant.
• Aerospace experience or familiarity with engineering, CAD, analytics, visualization, or flight-test workflows.

Culture & Benefits

• Onsite work in Mojave, California, with a 9/80 schedule and no travel required.
• Medical, dental, vision, and prescription drug healthcare benefits.
• Paid maternity and parental leave.
• 50% company match per contributed dollar into a 401(k), up to $11,500.
• Tuition reimbursement and an equal-opportunity workplace.