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Machine Learning Ops Engineer

At Zone 5 Technologies, we're redefining what's possible in unmanned aircraft systems. Our team of engineers and innovators is developing cutting-edge autonomous solutions that pus

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Zone 5 Technologies Source published Sep 20, 2026 Verified 10 hours ago
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Overview

At Zone 5 Technologies, we're redefining what's possible in unmanned aircraft systems. Our team of engineers and innovators is developing cutting-edge autonomous solutions that pus

Full job description

At Zone 5 Technologies, we're redefining what's possible in unmanned aircraft systems. Our team of engineers and innovators is developing cutting-edge autonomous solutions that push the boundaries of UAS technology - solving complex challenges that matter. We're building the future of UAS capabilities, and we're looking for exceptional talent to join us. If you're driven by hard problems, energized by rapid innovation, and ready to make an impact on next-generation flight systems, you belong here. We are investing in in-house LLM tooling and are hiring a dedicated MLOps Engineer to help grow it. You will build AI-powered capabilities—retrieval-augmented generation, tool integrations, and agentic workflows—and turn them into reliable services used by teams across the company. This is a builder's role focused on shipping new capability.   The role spans a broad stack. We welcome both generalists and specialists—you do not need every skill listed below. Tell us where you are strong and where you want to grow. The center of gravity is LLM application development, retrieval quality, and agent design.   Responsibilities:   LLM Applications, RAG & Agents   Design and build new LLM-powered tools and agentic workflows that automate real work and improve productivity across the company   Extend and improve our RAG systems—ingestion, chunking, embedding, retrieval, ranking, and evaluation—to raise answer quality   Structure retrieval around the organization's information hierarchy so that relevance and access boundaries improve together   Build tool integrations that connect LLMs to internal systems and data sources   Design agents that act safely against real systems, with appropriate guardrails, human-in-the-loop where warranted, and clear failure behavior   Establish evaluation and testing frameworks to measure quality, catch regressions, and guide iteration   Partner with teams across the company to identify high-value use cases and turn them into deployed tools   Service Deployment & AI Infrastructure   Deploy AI tools and services for teams across the company, taking them from prototype to reliable production   Build and operate the infrastructure that hosts models, tools, and supporting services on Kubernetes   Manage model serving, inference endpoints, and the APIs and gateways around them   Implement monitoring, logging, and usage observability so we understand how tools perform and get used   Access, Security & Data Boundaries   Ensure retrieval and agent tools respect the same access boundaries as the underlying systems—no cross-team or cross-project data leakage   Integrate with existing identity and permission systems so tools honor who is allowed to see what   Apply data-handling practices appropriate to a defense environment   Treat access control as a first-class design concern in every tool, not an afterthought   Automation & Data Operations   Build CI/CD pipelines for AI tools, services, and agents   Automate provisioning and configuration with Ansible and infrastructure-as-code practices   Build data pipelines to ingest, transform, and index content for RAG and AI applications   Manage vector databases and other stores backing retrieval and AI workloads, including versioning and quality checks   Maintain reproducible environments across development, staging, and production   Qualifications:   Bachelor's in Computer Science, Software Engineering, Data Engineering, or related field – equivalent industry experience also welcome   3-6+ years of experience in MLOps, software, platform, or backend engineering (relevant depth matters more than exact years)   Strong proficiency in Python and comfort building, shipping, and operating services   Experience building LLM-powered applications—working with LLM APIs or self-hosted models, prompts, and tool/function calling   Hands-on experience with Kubernetes and containerized deployment   Solid understanding of CI/CD, infrastructure-as-code, and production service reliability   Awareness of access control and data-boundary concerns when connecting tools to sensitive internal systems   Demonstrated ability to learn quickly and work across unfamiliar parts of the stack   Depth in at least one core area—LLM application development, RAG/retrieval, agent design, or AI infrastructure—with genuine interest in growing into the others   Preferred:   Hands-on experience with RAG systems, embeddings, and vector databases (pgvector, Qdrant, Weaviate, Milvus, or similar)   Experience designing and shipping agentic workflows, including tool use, orchestration, and guardrails   Familiarity with the Model Context Protocol (MCP) or similar tool-integration frameworks for LLMs   Experience integrating LLM tools with enterprise systems (productivity suites, business systems, or developer platforms) via their APIs   Knowledge of LLM evaluation, prompt engineering, and quality/regression measurement   Experience serving models and optimizing inference (vLLM, TGI, Triton, or similar)   Familiarity with agent/orchestration libraries (LangChain, LlamaIndex, or equivalent)   Experience with Ansible for configuration management and automation   Experience implementing identity, authentication, and fine-grained authorization (OAuth, SSO, RBAC)   Observability experience for AI/ML workloads, including usage and quality metrics   GPU infrastructure and scheduling experience for training or inference   Understanding of security and data-handling requirements in regulated or defense environments   Ability to obtain or maintain a security clearance   Pay range for this role $140,000 — $175,000 USD What's in it for you: Benefits:  Competitive total compensation package  Comprehensive benefit package options include medical, dental, vision, life, and more. 401k with company-match  3 weeks of paid time off each year 40 hours of sick time 12 annual company holidays Why Join Zone 5 Technologies? Innovative Environment: Work on cutting-edge technology that is shaping the future of defense and aerospace. Collaborative Culture: Join a team of passionate professionals dedicated to pushing the boundaries of what’s possible. Career Growth: Opportunities for professional development and career advancement. If you are passionate about unmanned aircraft technology and want to be a part of a dynamic and growing company, we would love to hear from you. Apply today and join the Zone 5 Technologies team!  In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to complete the required employment eligibility verification form upon hire. Zone 5 Technologies is a federal contractor and participates in E-Verify to confirm employment eligibility. As required by law, we will verify the identity and employment authorization of all new employees using the E-Verify system. Learn more about your rights and responsibilities under E-Verify:  https://www.e-verify.gov .

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