MaxLinear is seeking a highly motivated Artificial Intelligence Engineer to evaluate and integrate cutting-edge AI technologies into the semiconductor engineering workflows. This role sits at the intersection of AI innovation, engineering productivity, and enterprise-scale deployment, helping shape how modern AI systems are operationalized across teams. You will play a critical role in identifying high-impact use cases, benchmarking AI platforms, and delivering scalable, secure solutions that drive measurable business value. In this role, you will focus on the following:

• Evaluate AI platforms and large language models (LLMs), including GPT, Claude, Gemini, and SWE-class systems
• Contribute to the design and execution of benchmarks to measure quality of results (QoR), productivity gains, and scalability
• Identify strengths, limitations, and optimal use cases across AI tools and architectures
• Partner with cross-functional teams to deploy solutions across multiple domains
• Validate and implement AI-driven solutions within real-world semiconductor engineering workflows
• Partner with engineering to translate engineering use cases into production-ready AI capabilities
• Partner with internal teams to develop and analyze ROI and cost-performance tradeoffs across cloud and on-prem deployment models
• Provide data-driven recommendations on AI platform selection and scaling strategies
• Optimize resource utilization for maximum business impact
• Design and support LLM deployments across hybrid environments (cloud and on-prem)
• Integrate with enterprise data platforms, including data lakes and MCP gateway architectures
• Ensure performance, reliability, and scalability of deployed AI systems
• Implement best practices based on NIST and OWASP frameworks
• Define AI usage guardrails, governance models, and compliance policies
• Ensure enterprise-grade security and responsible AI adoption

• Experience working with large language models (LLMs) and AI/ML systems
• Strong analytical skills with experience in benchmarking, evaluation, or performance analysis
• Experience with cloud platforms (AWS, Azure, GCP) and/or on-prem infrastructure
• Ability to translate technical capabilities into business value
• Experience integrating AI into engineering or semiconductor workflows
• Familiarity with data platforms, pipelines, and large-scale data processing
• Knowledge of AI security, governance, and compliance frameworks
• Hands-on experience with model deployment, APIs, and system integration
• BS in Electrical Engineering or related