Lenovo

About the Company

Lenovo is a US$57 billion revenue global technology powerhouse, ranked #248 in the Fortune Global 500, and serving millions of customers every day in 180 markets. Focused on a bold vision to deliver Smarter Technology for All, Lenovo has built on its success as the world’s largest PC company with a full-stack portfolio of AI-enabled, AI-ready, and AI-optimized devices (PCs, workstations, smartphones, tablets), infrastructure (data center, storage, edge, high performance computing and software defined infrastructure), software, solutions, and services. Lenovo’s continued investment in world-changing innovation is building a more equitable, trustworthy, and smarter future for everyone, everywhere. Lenovo is listed on the Hong Kong stock exchange under Lenovo Group Limited (HKSE: 992) (ADR: LNVGY). To find out more visit https://www.lenovo.com, and read about the latest news via our StoryHub at https://news.lenovo.com/.

To learn more about our career opportunities, visit our careers page at http://jobs.lenovo.com/.

Listed Jobs

Company Name

Lenovo

Job Title

AI Knowledge Engineer

Job Description

Job Title: AI Knowledge Engineer Role Summary: Design, implement, and evolve knowledge architectures that integrate semantic web, vector/graph databases, and large language models (LLMs) to deliver explainable, grounded AI across the product stack. Expectations: Deliver robust knowledge models and GraphRAG pipelines that enhance AI performance, maintain high-quality semantic layers, and drive innovation in ontology engineering and multimodal data integration. Key Responsibilities: - Architect and deploy knowledge graphs using semantic web technologies and graph databases. - Integrate knowledge graphs with LLMs via GraphRAG architectures to ground AI responses. - Research dynamic ontology engineering, leveraging LLM-assisted schema evolution and automated knowledge extraction. - Build semantic layers and data fabrics to unify multimodal data across AI services. - Collaborate with data, ML, and product teams to embed knowledge models into application workflows. - Stay current on semantic AI research and emerging RAG patterns, translating insights into production solutions. Required Skills: - 3+ years of experience in knowledge engineering, semantic web, or related domains. - Proficiency in Python, Java, or Kotlin with advanced use of graph query languages (SPARQL, Cypher). - Strong understanding of vector databases, graph databases, and semantic web standards. - Experience designing and implementing GraphRAG or similar LLM‑KG integration architectures. - Capable of developing ontology models and automated knowledge extraction pipelines. - Excellent analytical, problem‑solving, and communication skills. Required Education & Certifications: - Bachelor’s degree in Engineering, Computer Science, or a related field. - Relevant certifications in data modeling, graph databases, or AI/ML (preferred but not required).

Chicago, United states

On site

22-12-2025

Company Name

Lenovo

Job Title

Engineer, AI Model

Job Description

**Job Title:** Engineer, AI Model **Role Summary:** Develop, train, and evaluate large-scale generative AI models (LLMs, LVMs, LMMs) including fine‑tuning, reinforcement learning, and quantization. Build data and model pipelines, experiment with training techniques, and collaborate with cross‑functional teams to integrate AI models into products. **Expectations:** - Design and implement end‑to‑end training pipelines for large models. - Create data augmentation and preprocessing workflows to enhance dataset diversity. - Conduct supervised fine‑tuning, RLHF (e.g., DPO, KTO), and reinforcement‑learning experiments. - Apply quantization and LoRA methods for efficient deployment across hardware. - Stay current with state‑of‑the‑art research and contribute to internal tooling. - Communicate results and collaborate effectively with engineers and researchers. **Key Responsibilities:** - Build and maintain training and evaluation pipelines for generative AI. - Develop data augmentation scripts and manage large training datasets. - Implement SFT strategies and RLHF algorithms for task‑specific performance. - Design reward functions and sampling methods for large‑scale RL training. - Evaluate and optimize model size vs. inference speed via quantization. - Apply Low‑Rank Adaptation techniques for resource‑efficient fine‑tuning. - Run experiments, tune hyper‑parameters, and document findings. - Contribute to internal infrastructure and tooling for model training and testing. **Required Skills:** - Proficiency in Python; strong coding practices. - Experience with PyTorch or comparable deep‑learning frameworks. - Solid grasp of machine‑learning fundamentals (supervised, unsupervised, RL). - Hands‑on experience with large language/vision models and transformer architectures. - Ability to design, execute, and analyze experiments; data‑processing expertise. - Knowledge of quantization, LoRA, and RLHF techniques. - Strong problem‑solving, communication, and teamwork abilities. **Required Education & Certifications:** - Master’s degree in Computer Science, Machine Learning, or a related field *or* equivalent experience. - Minimum 2 years of relevant professional experience (or 4 years without a master’s). - No specific certifications required; demonstrated expertise through projects/experience is essential.

North carolina, United states

On site

Junior

23-01-2026

Company Name

Lenovo

Job Title

AI/ML Orchestration Engineer

Job Description

Job title: AI/ML Orchestration Engineer Role Summary: Design, implement, and optimize agentic orchestration frameworks that convert large language models into autonomous, multi‑agent systems capable of complex reasoning, tool integration, and real‑world action across devices. Expectations: Lead the creation of production‑grade AI orchestration infrastructure; ensure scalability, robustness, observability, and safety; collaborate with cross‑functional teams to deliver adaptive experiences. Key Responsibilities: - Design and implement agentic orchestration frameworks using LangChain, LangGraph, or custom solutions. - Build tool‑integration ecosystems based on function‑calling standards such as the Model Context Protocol (MCP). - Architect distributed reasoning, planning, and execution pipelines for coordinated multi‑agent workflows. - Develop memory and context management systems that support long‑term agent coherence and personalization. - Create evaluation frameworks to assess agent reliability, safety, and performance. - Maintain robust error handling, observability, and performance tuning for production‑grade AI systems. - Iterate on product features and architecture in collaboration with product, data, and engineering teams. Required Skills: - Minimum 3 years in AI/ML systems, with 3 years focused on LLM applications or agent frameworks. - Strong experience with agentic AI architectures (planning, reasoning, tool use, memory systems). - Proven track record building production AI systems at scale, with robust error handling and observability. - Proficiency in Python; knowledge of Java, Kotlin, async programming, and API design is preferred. - Familiarity with prompt engineering, Retrieval‑Augmented Generation (RAG), fine‑tuning, and LLM orchestration patterns. - Strong performance optimization mindset and creative problem‑solving ability. Required Education & Certifications: - Bachelor’s degree in Engineering, Computer Science, or a related technical field.

Chicago, United states

On site

02-02-2026