Machine Learning Ops Engineer

🔥 13 hours ago

🇺🇸 United States – Remote

💵 $140k - $175k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 Machine Learning Engineer

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ZS

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1983

🏥 Healthcare

📦 Logistics

📣 Marketing

Healthcare • Logistics • Marketing

ZS is a consulting and technology services firm that specializes in providing analytics and solutions specifically for the healthcare and life sciences industries. Their expertise spans across various sectors, including pharmaceuticals, medical technology, and health plans, enabling organizations to enhance their commercial effectiveness and drive results through data-driven strategies and innovative solutions. With a commitment to transforming healthcare, ZS partners with clients to bridge gaps and improve patient experiences through digital health advancements and intelligent process automation.

📋 Description

• Design and build LLM-powered tools and agentic workflows that automate work and improve productivity • Extend and improve RAG systems, including ingestion, chunking, embedding, retrieval, ranking, and evaluation • Structure retrieval around the organization’s information hierarchy while improving relevance and access boundaries • Build tool integrations connecting LLMs to internal systems and data sources • Design safe agents with guardrails, human-in-the-loop processes, and clear failure behavior • Establish evaluation and testing frameworks to measure quality and catch regressions • Partner with teams across the company to identify high-value use cases and deploy tools • Deploy AI tools and services from prototype to reliable production • Build and operate Kubernetes infrastructure hosting models, tools, and supporting services • Manage model serving, inference endpoints, APIs, and gateways • Implement monitoring, logging, and usage observability • Ensure retrieval and agent tools respect access boundaries and prevent data leakage • Integrate identity and permission systems so tools honor access rights • Apply defense-appropriate data-handling practices • Build CI/CD pipelines for AI tools, services, and agents • Automate provisioning and configuration with Ansible and infrastructure-as-code • Build data pipelines to ingest, transform, and index content for RAG and AI applications • Manage vector databases and other stores supporting retrieval and AI workloads • Maintain reproducible development, staging, and production environments

🎯 Requirements

• 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 • Strong proficiency in Python and comfort building, shipping, and operating services • Experience building LLM-powered applications, including 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 interest in growing into the others • Ability to obtain or maintain a security clearance • Preferred: hands-on experience with RAG systems, embeddings, and vector databases • Preferred: experience designing and shipping agentic workflows, including tool use, orchestration, and guardrails • Preferred: familiarity with Model Context Protocol (MCP) or similar tool-integration frameworks • Preferred: experience integrating LLM tools with enterprise systems via APIs • Preferred: knowledge of LLM evaluation, prompt engineering, and quality/regression measurement • Preferred: experience serving models and optimizing inference with vLLM, TGI, Triton, or similar • Preferred: familiarity with LangChain, LlamaIndex, or equivalent • Preferred: experience with Ansible for configuration management and automation • Preferred: experience implementing identity, authentication, and fine-grained authorization, including OAuth, SSO, and RBAC • Preferred: observability experience for AI/ML workloads • Preferred: GPU infrastructure and scheduling experience • Preferred: understanding of security and data-handling requirements in regulated or defense environments

🏖️ Benefits

• Competitive total compensation package • Comprehensive benefit package options including 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 • Professional development and career advancement opportunities • Innovative environment focused on cutting-edge defense and aerospace technology • Collaborative culture

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