Advanced AI Scientist

Zebra Technologies•Austin, TX
•Hybrid

About The Position

At Zebra, we are a community of innovators who come together to create new ways of working. United by curiosity and a culture of caring, we develop smart solutions that anticipate our customer’s and partner’s needs and solve their challenges. Being part of Zebra Nation means you are seen, heard, valued, and respected. Drawing from our unique perspectives, we collaborate to deliver on our purpose. Here you are part of a team pushing boundaries today to redefine the work of tomorrow for organizations, their employees, and those they serve. You’ll have opportunities to learn and lead in a forward-thinking environment, defining your path to a fulfilling career while channeling your skills toward causes you care about—locally and globally. Come make an impact every day at Zebra. What We're Looking For: The Advanced AI Scientist is a highly experienced technical individual contributor within Product and Forward Deployed Engineering, responsible for developing and delivering AI/GenAI solutions for strategic customers. The role works closely with customers, Product, Engineering, and cross-functional teams to translate complex business challenges into production-ready solutions with measurable business impact.

Requirements

  • Master’s or Ph.D in mathematics, statistics, computer science, computer engineering, operations research, or related field.
  • Minimum 8+ years' experience in data science, machine learning, or software engineering required.

Nice To Haves

  • Deep hands-on experience with Generative AI, LLMs, foundation models, RAG, multimodal AI, prompt/context engineering, and AI application development.
  • Strong expertise in agentic AI, including multi-agent systems, orchestration, planning and execution, tool calling, agent memory/state, MCP/A2A, and emerging agentic patterns.
  • Experience building reliable AI systems through evaluation, benchmarking, guardrails, hallucination mitigation, observability, and continuous improvement.
  • Strong software engineering skills, with proficiency in Python and/or languages such as Java, Go, or TypeScript.
  • Experience deploying and operating production AI systems, with a focus on reliability, security, performance, scalability, observability, and cost efficiency.
  • Demonstrated ability to rapidly experiment with emerging AI technologies and translate concepts into practical, production-ready solutions that deliver measurable customer outcomes.

Responsibilities

  • Develop and deliver AI/GenAI solutions using LLMs, foundation models, RAG, multimodal AI, and emerging agentic technologies to solve complex customer problems.
  • Build advanced agentic applications using multi-agent orchestration, planning and execution, tool calling, MCP/A2A, agent memory and state, and adaptive execution patterns.
  • Engineer reliable AI systems through model selection, prompt and context engineering, evaluation, benchmarking, guardrails, robust tool execution, and continuous improvement.
  • Develop AI evaluation and observability capabilities to measure task completion, agent behavior, tool use, quality, reliability, latency, and cost.
  • Develop production-grade software using Python, Java, Go, or TypeScript, integrating AI capabilities with enterprise applications, APIs, data, and customer workflows.
  • Deploy, operate, troubleshoot, and optimize AI solutions for security, reliability, performance, scalability, cost efficiency, and user experience.
  • Lead technical delivery for strategic customers, from problem discovery and rapid prototyping through production deployment, adoption, and continuous improvement.
  • Collaborate with customers, Product, Engineering, and cross-functional teams to translate business needs into technical solutions, communicate tradeoffs, and influence product direction.
  • Drive innovation by evaluating emerging AI technologies and translating customer learnings into reusable frameworks, tools, engineering practices, and product capabilities.

Benefits

  • healthcare
  • wellness
  • inclusion networks
  • continued learning and development offerings
  • community service days
  • parental leave
  • employee assistance program
  • paid time off
  • hybrid work
  • adaptable hours
  • Summer Flex Fridays
  • Focus Fridays
  • annual companywide well-being day
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