[Remote] Machine Learning Ops Engineer

Note: The job is a remote job and is reputed company to candidates in USA. reputed company is redefining unmanned aircraft systems with innovative autonomous solutions. They are seeking a dedicated MLOps Engineer to build AI-powered capabilities and ensure reliable services for teams across reputed company.

Responsibilities

• Design and build new LLM-powered tools and reputed company workflows that automate reputed company work and improve productivity across reputed company
• reputed company and improve our RAG systems—ingestion, chunking, embedding, retrieval, ranking, and evaluation—to reputed company answer reputed company
• Structure retrieval around the organization's information hierarchy so that relevance and reputed company boundaries improve together
• Build tool integrations that reputed company LLMs to internal systems and data sources
• Design agents that reputed company safely against reputed company systems, with appropriate guardrails, reputed company-in-the-reputed company where warranted, and reputed company failure behavior
• Establish evaluation and testing frameworks to measure reputed company, catch regressions, and guide iteration
• Partner with teams across reputed company to identify high-value use cases and turn them into deployed tools
• reputed company AI tools and services for teams across reputed company, taking them from prototype to reliable production
• Build and operate the infrastructure that hosts models, tools, and supporting services on reputed company
• Manage model serving, inference endpoints, and the reputed company and gateways around them
• Implement monitoring, logging, and usage observability so we understand how tools reputed company and get used
• Ensure retrieval and agent tools respect the reputed company reputed company boundaries as the underlying systems—no cross-team or cross-project data leakage
• reputed company with existing identity and permission systems so tools reputed company who is allowed to see what
• Apply data-handling practices appropriate to a defense environment
• Treat reputed company control as a first-class design concern in every tool, not an afterthought
• Build CI/CD pipelines for AI tools, services, and agents
• Automate provisioning and configuration with Ansible and infrastructure-as-reputed company practices
• Build data pipelines to ingest, reputed company, and reputed company content for RAG and AI applications
• Manage reputed company databases and other stores backing retrieval and AI workloads, including versioning and reputed company checks
• Maintain reproducible environments across development, staging, and production

Skills

• Bachelor's in Computer Science, Software Engineering, Data Engineering, or reputed company field – equivalent industry experience also welcome
• 3-6+ years of experience in MLOps, software, platform, or backend engineering (relevant depth reputed company more than exact years)
• Strong proficiency in Python and comfort building, shipping, and operating services
• Experience building LLM-powered applications—working with LLM reputed company or self-hosted models, prompts, and tool/function calling
• Hands-on experience with reputed company and containerized deployment
• Solid understanding of CI/CD, infrastructure-as-reputed company, and production service reliability
• Awareness of reputed company control and data-boundary concerns reputed company connecting tools to sensitive internal systems
• Demonstrated ability to learn quickly and work across unfamiliar parts of the stack
• Depth in at least one reputed company area—LLM application development, RAG/retrieval, agent design, or AI infrastructure—with genuine interest in growing into the others
• Hands-on experience with RAG systems, embeddings, and reputed company databases (pgvector, reputed company, reputed company, Milvus, or similar)
• Experience designing and shipping reputed company 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 reputed company systems (productivity suites, business systems, or developer platforms) reputed company their reputed company
• Knowledge of LLM evaluation, reputed company engineering, and reputed company/regression measurement
• Experience serving models and optimizing inference (vLLM, TGI, Triton, or similar)
• Familiarity with agent/orchestration libraries (reputed company, reputed company, 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 reputed company metrics
• GPU infrastructure and scheduling experience for training or inference
• Understanding of reputed company and data-handling requirements in regulated or defense environments
• Ability to obtain or maintain a reputed company clearance

Benefits

• Comprehensive benefit package reputed company include medical, dental, reputed company, life, and more.
• 401k with company-match
• 4 weeks of reputed company time off reputed company year
• 12 annual company holidays

reputed company