MLOps Engineer

Quick Facts

• Role: MLOps Engineer (AI Platform / MLOps)

• Focus: Infrastructure and integrations to operationalize AI/LLM and RAG workloads in production

• Location: Mojave, CA

Description

Design, deploy, and operate reliable infrastructure for ML, LLM, and RAG workloads, with observability, integrations, and developer tools that enable production AI for vehicle design, manufacture, and flight test teams. Host and optimize RAG systems (including Qdrant), build logging/monitoring and alerting, and run AI workloads in AWS while creating APIs, plugins, SDKs, and CLI tools for internal users. Evaluate and integrate COTS, third-party services, open-source tools, and internal applications to deliver maintainable, user-focused solutions.

Responsibilities

• Design, deploy, and operate reliable, observable infrastructure for ML/LLM/RAG workloads in AWS

• Host, maintain, monitor, and optimize RAG systems and retrieval infrastructure; build logging, observability, and alerting for health/performance/cost/reliability

• Serve as an MLOps subject matter expert for model deployment, inference services, resource utilization, and production support

• Integrate and support COTS products, third-party services, open-source tools, and custom AI capabilities with shared responsibility for monitoring/security/cost/performance/reliability

• Develop APIs, plugins, reusable integrations, and developer tooling (e.g., OpenWebUI, Hugging Face, Wilbur)

• Collaborate with stakeholders to build team-specific AI integrations/workflows and connect AI services to existing frontend/web infrastructure (e.g., Streamlit, NGINX, reverse proxies/load balancing)

• Work 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)

• Programming experience in Python, Rust, C, MATLAB, or equivalent

• Experience developing and integrating APIs/services/plugins/software interfaces

• Containerization and orchestration experience (Docker, Kubernetes, Dagster, or equivalent)

• Logging, monitoring, troubleshooting, and production support experience

• CLI tools and shell scripting (Bash or Windows batch scripting)

• DevSecOps and CI/CD experience (Jenkins, GitLab, Bamboo, or equivalent)

• Experience integrating COTS products, third-party services, APIs, and/or open-source software into production

• Ability to collaborate with stakeholders to evaluate options and deliver practical solutions

• BS in a relevant field (CS/Engineering/Data Science) or equivalent applicable experience

• 5–10 years professional experience in a related discipline (software/cloud/data/MLOps/AI)

Benefits

• Healthcare (medical, dental, vision, prescription drugs)

• Paid Maternity and Parental Leave

• 401(k) savings plan: 50% match per contributed dollar, up to $11,500

• Tuition reimbursement