{"id":3220057,"url":"https://alion.io/job/metasys-aiml-engineer-internship","title":"AI/ML Engineer Internship","company":{"id":3856814,"name":"Metasys","domain":"metasysglobal.com","url":"https://alion.io/company/metasys","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"intern","employment_type":"internship","work_mode":"remote","remote_scope":"worldwide","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":[],"countries":[],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"AutoGen","optional":false},{"name":"Docker","optional":false},{"name":"Fine-tuning","optional":false},{"name":"Jira","optional":false},{"name":"LangChain","optional":false},{"name":"LlamaIndex","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Machine Learning","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"Nest.JS","optional":false},{"name":"Node JS","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"RAG","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"Slack","optional":false},{"name":"TensorFlow","optional":false},{"name":"JavaScript","optional":true}],"status":"live","first_seen_at":"2026-10-24T23:47:17Z","employer_posted_date":null,"last_verified_at":"2026-10-24T23:47:17Z","board_verified":false,"closed_at":null,"days_open":4,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":4},"description":"Overview: Building Autonomous AI AgentsThe AI/ML Engineer with an AI Agent Focus is a specialized role dedicated to designing, building, and deploying autonomous AI agents that handle complex business processes independently. You will be at the forefront of integrating cutting-edge Large Language Models (LLMs) and reasoning frameworks into our e-commerce and supply chain ecosystem, driving efficiency and innovation through intelligent automation.\nInternship DetailsDuration: 3 months \nStart Date: ImmediateLocation: RemoteStipend: None initially. Based on your first-quarter performance, you may be offered a paid full-time opportunity, or even be absorbed directly by the client as an FTE.\nKey Responsibilities & Core ProjectsYou will be responsible for the full lifecycle of agent development, from initial design to production optimization and monitoring.\n\nAgent Architecture & Development: Design and build autonomous AI agent architectures utilizing LLMs, advanced reasoning frameworks, and decision-making systems to achieve specific business goals (e.g., customer support automation, sales assistance, workflow optimization).\n\nBusiness Process Automation: Create agents that integrate directly into the platform to automate critical supply chain and administrative tasks, such including:\n\nCustomer Support Agents integrated into the e-commerce storefront.\n\nInternal Workflow Automation agents (e.g., Slack integration, Jira automation).\n\nMulti-Agent Systems: Implement and orchestrate multi-agent systems where specialized agents collaborate to solve complex, multi-step problems across different modules (MES, WMS, OMS).\n\nAdvanced Agent Capabilities: Develop and implement memory systems, sophisticated context management, and tool integration strategies (allowing agents to use internal APIs, search, or code execution) to enhance agent efficacy.\n\nModel Optimization: Implement techniques for agent improvement, including fine-tuning of LLM models and applying concepts from Reinforcement Learning for optimal decision-making.\n\nSafety & Monitoring: Implement safety guardrails, define ethical usage guidelines, and build robust monitoring systems (collaborating with MLOps) to track and analyze agent behavior and performance in production.\n\nRequired Technologies & ToolsCandidates must possess deep experience in machine learning, LLM technology, and production deployment:\n\nLLM/Agent Frameworks: Mandatory hands-on expertise with agent construction frameworks like LangChain, LlamaIndex, and AutoGen.\n\nProgramming & ML: Expert proficiency in Python and standard ML/Deep Learning libraries (e.g., PyTorch, TensorFlow).\n\nData & APIs: Experience preparing data for model fine-tuning and integrating agents via API endpoints into production services (Node.js/NestJS).\n\nDeployment: Familiarity with MLOps concepts (versioning, deployment) and containerization (Docker) for agent deployment.\n\nDatabases: Understanding of vector databases and retrieval augmented generation (RAG) techniques.\n\n Supply Chain Integration (Domain Focus)You will integrate intelligent agents directly into our core supply chain and data systems.\n\nData Analysis Agents: Build agents capable of complex data analysis and insight generation using aggregated data from MES, WMS, and OMS.\n\nE-commerce Integration: Deploy agents that assist users directly within the e-commerce platform by accessing real-time catalog and inventory data.\n\nSuccess Metrics & Career PathPerformance will be measured by:\nAgent Autonomy: Measurable increase in the percentage of business tasks handled end-to-end by autonomous agents.\n\nBusiness Impact: Quantifiable improvements in metrics driven by the agents (e.g., reduced customer support response time, increased sales conversion).\n\nModel Performance: Accuracy and efficiency of fine-tuned models and the reliability of multi-agent systems.\n\nMentorship Structure: Reports to the Head of Technology/CTO, working closely with the Data Architect and MLOps Engineer to productionize and scale agent capabilities.\nOriginally posted on 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