Forward Deployed AI Research Scientist
Confirmed on the employer's own hiring board on Oct 24, 2026. First seen by Alion on Oct 12, 2026. AMD scores B on the Alion truth index.
WHAT YOU DO AT AMD CHANGES EVERYTHING
At AMD, our mission is to build great products that accelerate next-generation computing experiences-from AI and data centers, to PCs, gamingand embedded systems. Grounded in a culture of innovation and collaboration, we believe real progress comes from bold ideas, human ingenuityand a shared passion to create something extraordinary. When you join AMD, you’lldiscover the real differentiator is our culture. We push the limits of innovation to solve the world’s most important challenges-striving for execution excellence, while being direct, humble, collaborative, and inclusive of diverse perspectives. Join us as we shape the future of AI and beyond.Together, we advance your career.
THE ROLE:
We are hiring Forward Deployed AI Research Scientist to help bring advanced AI capabilities into high-impact engineering and customer-facing workflows. This role combines applied AI research, technical strategy, prototyping, and field-facing collaboration. You will work closely with internal engineering teams and strategic external partners to identify valuable problems, shape them into tractable AI research and engineering efforts, and drive them toward measurable outcomes.
The role is designed to scale a technical-business bridge across AMD: translating customer and partner needs into AI research directions, translating AI capabilities into engineering value, and helping teams align on what can be built, measured, and delivered.,
THE PERSON:
You are a research-minded technical leader who can operate in ambiguous, high-stakes environments. You can speak credibly with AI researchers, software engineers, hardware engineers, executives, and partner teams. You are equally comfortable reading papers, shaping experiments, building prototypes, writing crisp technical narratives, and helping stakeholders understand what matters.
KEY RESPONSIBILITIES:
- Work with internal and external stakeholders to identify high-value AI opportunities in compute, systems, software, and hardware engineering workflows.
- Translate partner and customer needs into research questions, technical plans, evaluation criteria, and prototype paths.
- Prototype and evaluate modern AI methods for engineering tasks, including agentic workflows, tool use, code generation, debugging, optimization, retrieval, and learning from feedback.
- Partner with research and engineering teams to define metrics, evals, benchmarks, and acceptance criteria for AI-assisted workflows.
- Build technical narratives, demos, and decision materials that help senior stakeholders understand tradeoffs, progress, risks, and strategic value.
- Support strategic deals and collaborations by serving as a credible technical bridge between business goals and AI engineering reality.
- Capture recurring customer and partner needs and turn them into reusable insights for product, research, platform, and engineering roadmaps.
- Mentor teams on practical AI methods and help raise the quality of AI experimentation, evaluation, and communication across the organization.
TECHNICAL FOCUS AREAS:
- Applied AI research for engineering workflows where correctness, performance, latency, reliability, and explainability matter.
- Agentic systems that use tools, tests, profilers, simulators, validation systems, and structured feedback.
- Evaluation design for ambiguous or high-value tasks, including objective graders, human-in-the-loop review, and LLM-as-judge methods where appropriate.
- AI systems for code understanding, code generation, optimization, debugging, knowledge retrieval, and workflow automation.
- Technical-business translation for strategic customers, partners, engineering leaders, and cross-functional teams.
REQUIRED QUALIFICATIONS:
- Strong background in AI, machine learning, systems, or applied research, with ability to turn ideas into prototypes and measurable experiments.
- Experience with modern generative AI methods, LLMs, agents, tool use, retrieval, post-training, evaluation, or applied ML systems.
- Strong programming ability in Python and familiarity with ML frameworks such as PyTorch, JAX, TensorFlow, or similar.
- Ability to work with technical stakeholders across software, hardware, infrastructure, research, product, and business teams.
- Excellent communication skills, including the ability to explain complex AI and systems topics clearly to both technical and executive audiences.
PREFERRED EXPERIENCE:
- Experience in forward-deployed engineering, customer engineering, applied research, technical partnerships, solutions architecture, or strategic technical programs.
- Experience with GPU systems, CPU performance, compilers, distributed training/inference, hardware/software co-design, or performance engineering.
- Experience designing benchmarks, evals, experiment platforms, or metrics for AI systems.
- Publications, open-source contributions, technical blogs, demos, or shipped AI systems are a plus.
- Familiarity with semiconductor, datacenter, AI infrastructure, or high-performance computing environments is a strong plus.
ACADEMIC CREDENTIALS:
Bachelor's degree is required preferrably in Computer Science, Computer Engineering, Electrical Engineering, Machine Learning, or related field, or equivalent practical experience. Master's preferred; PhD is a plus, especially in AI, ML systems, computer systems, GPU computing, or hardware/software co-design.
#LI-BM1
#LI-Hybrid
Benefits offered are described: AMD benefits at a glance.
AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants’ needs under the respective laws throughout all stages of the recruitment and selection process.
AMD may use Artificial Intelligence to help screen, assess or select applicants for this position. AMD’s “Responsible AI Policy” is available here.
This posting is for an existing vacancy.
THE ROLE:
We are hiring Forward Deployed AI Research Scientist to help bring advanced AI capabilities into high-impact engineering and customer-facing workflows. This role combines applied AI research, technical strategy, prototyping, and field-facing collaboration. You will work closely with internal engineering teams and strategic external partners to identify valuable problems, shape them into tractable AI research and engineering efforts, and drive them toward measurable outcomes.
The role is designed to scale a technical-business bridge across AMD: translating customer and partner needs into AI research directions, translating AI capabilities into engineering value, and helping teams align on what can be built, measured, and delivered.,
THE PERSON:
You are a research-minded technical leader who can operate in ambiguous, high-stakes environments. You can speak credibly with AI researchers, software engineers, hardware engineers, executives, and partner teams. You are equally comfortable reading papers, shaping experiments, building prototypes, writing crisp technical narratives, and helping stakeholders understand what matters.
KEY RESPONSIBILITIES:
- Work with internal and external stakeholders to identify high-value AI opportunities in compute, systems, software, and hardware engineering workflows.
- Translate partner and customer needs into research questions, technical plans, evaluation criteria, and prototype paths.
- Prototype and evaluate modern AI methods for engineering tasks, including agentic workflows, tool use, code generation, debugging, optimization, retrieval, and learning from feedback.
- Partner with research and engineering teams to define metrics, evals, benchmarks, and acceptance criteria for AI-assisted workflows.
- Build technical narratives, demos, and decision materials that help senior stakeholders understand tradeoffs, progress, risks, and strategic value.
- Support strategic deals and collaborations by serving as a credible technical bridge between business goals and AI engineering reality.
- Capture recurring customer and partner needs and turn them into reusable insights for product, research, platform, and engineering roadmaps.
- Mentor teams on practical AI methods and help raise the quality of AI experimentation, evaluation, and communication across the organization.
TECHNICAL FOCUS AREAS:
- Applied AI research for engineering workflows where correctness, performance, latency, reliability, and explainability matter.
- Agentic systems that use tools, tests, profilers, simulators, validation systems, and structured feedback.
- Evaluation design for ambiguous or high-value tasks, including objective graders, human-in-the-loop review, and LLM-as-judge methods where appropriate.
- AI systems for code understanding, code generation, optimization, debugging, knowledge retrieval, and workflow automation.
- Technical-business translation for strategic customers, partners, engineering leaders, and cross-functional teams.
REQUIRED QUALIFICATIONS:
- Strong background in AI, machine learning, systems, or applied research, with ability to turn ideas into prototypes and measurable experiments.
- Experience with modern generative AI methods, LLMs, agents, tool use, retrieval, post-training, evaluation, or applied ML systems.
- Strong programming ability in Python and familiarity with ML frameworks such as PyTorch, JAX, TensorFlow, or similar.
- Ability to work with technical stakeholders across software, hardware, infrastructure, research, product, and business teams.
- Excellent communication skills, including the ability to explain complex AI and systems topics clearly to both technical and executive audiences.
PREFERRED EXPERIENCE:
- Experience in forward-deployed engineering, customer engineering, applied research, technical partnerships, solutions architecture, or strategic technical programs.
- Experience with GPU systems, CPU performance, compilers, distributed training/inference, hardware/software co-design, or performance engineering.
- Experience designing benchmarks, evals, experiment platforms, or metrics for AI systems.
- Publications, open-source contributions, technical blogs, demos, or shipped AI systems are a plus.
- Familiarity with semiconductor, datacenter, AI infrastructure, or high-performance computing environments is a strong plus.
ACADEMIC CREDENTIALS:
Bachelor's degree is required preferrably in Computer Science, Computer Engineering, Electrical Engineering, Machine Learning, or related field, or equivalent practical experience. Master's preferred; PhD is a plus, especially in AI, ML systems, computer systems, GPU computing, or hardware/software co-design.
#LI-BM1
#LI-Hybrid
Benefits offered are described: AMD benefits at a glance.
AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants’ needs under the respective laws throughout all stages of the recruitment and selection process.
AMD may use Artificial Intelligence to help screen, assess or select applicants for this position. AMD’s “Responsible AI Policy” is available here.
This posting is for an existing vacancy.