{"id":2911983,"url":"https://alion.io/job/amd-sr-forward-deployed-ai-engineer","title":"Sr. Forward Deployed AI Engineer","company":{"id":93,"name":"AMD","domain":"amd.com","url":"https://alion.io/company/amd","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Jibe","truth_index":{"grade":"B","score":75,"open_postings":162,"ghost_share":0,"stale_share":0.994,"repost_share":0,"time_to_fill_p50_days":29,"computed_at":"2026-10-26T05:57:25Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Santa Clara, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":175000,"max_usd":338000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":1332},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"AI Agents","optional":false},{"name":"C++","optional":false},{"name":"CUDA","optional":false},{"name":"DPO","optional":false},{"name":"Fine-tuning","optional":false},{"name":"GRPO","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Post-training","optional":false},{"name":"PPO","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"Reward Modeling","optional":false},{"name":"RLHF","optional":false},{"name":"Rust","optional":false},{"name":"SFT","optional":false},{"name":"TypeScript","optional":false},{"name":"Function Calling","optional":true},{"name":"Hugging Face","optional":true},{"name":"JAX","optional":true},{"name":"PyTorch","optional":true},{"name":"Ray","optional":true},{"name":"TensorFlow","optional":true},{"name":"TensorFlow C++","optional":true},{"name":"vLLM","optional":true}],"status":"live","first_seen_at":"2026-07-22T17:24:00Z","employer_posted_date":"2026-10-20","last_verified_at":"2026-10-27T00:07:26Z","board_verified":true,"closed_at":null,"days_open":96,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":95},"description":"WHAT YOU DO AT AMD CHANGES EVERYTHING\nAt 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.\nTHE ROLE:\nWe're looking for a Forward Deployed Research Engineer to build, evaluate, and deploy cutting-edge AI systems that solve complex engineering challenges for enterprise customers.\nThis is not a traditional Solutions Engineer or prompt engineering role. You'll combine deep software engineering, applied AI research, and customer engagement to develop production-ready AI systems using modern LLMs, reinforcement learning, agentic workflows, and post-training techniques.\nTHE PERSON:\nYou'll work directly with customers, researchers, and product teams to transform ambiguous engineering problems into scalable AI solutions. From rapid prototyping to production deployment, you'll help shape both customer success and the evolution of our AI platform.\nWhat Makes This Role Unique\nBuild AI systems that solve real-world engineering problems-not proof-of-concepts.\nWork across applied AI research, software engineering, and customer deployment.\nPartner directly with enterprise engineering teams to define, build, and validate AI solutions.\nInfluence future AI products by translating customer challenges into reusable platform capabilities.\nOwn projects end-to-end-from technical discovery and experimentation through deployment and measurable impact.\nKEY RESPONSIBILITIES:\nPartner with customer engineering teams to understand workflows, technical challenges, and opportunities for AI-driven automation.\nDesign, build, and deploy production-grade AI applications, LLM agents, and engineering automation solutions.\nDevelop evaluation frameworks, benchmarks, testing environments, and data pipelines to measure model quality and business impact.\nBuild and evaluate LLM post-training solutions, including supervised fine-tuning, reinforcement learning, preference optimization, and reward modeling.\nDiagnose and optimize AI system performance across models, data, infrastructure, orchestration, and tooling.\nCollaborate with AI researchers to validate new models and techniques in production environments.\nPresent technical solutions, architecture, and implementation strategies to engineering leaders, customers, and executive stakeholders.\nTransform recurring customer use cases into reusable AI infrastructure, frameworks, and platform capabilities.\nREQUIRED QUALIFICATIONS:\nStrong software engineering experience in Python and at least one systems language such as C++, Rust, C, TypeScript, CUDA, or HIP.\nProven experience building production AI or machine learning systems beyond prompt engineering or API integrations.\nHands-on experience with one or more of the following:LLM post-training\nReinforcement Learning (RLHF, PPO, DPO, GRPO, or similar)\nPreference Optimization\nReward Modeling\nModel or Agent Evaluation\nAI Training or Inference Infrastructure\n\nDeep understanding of transformer-based LLMs, inference, fine-tuning, retrieval, evaluation, and agent architectures.\nExperience designing reproducible evaluation frameworks using benchmarks, testing, and measurable performance metrics.\nStrong systems thinking, debugging, and problem-solving skills.\nExperience translating ambiguous technical requirements into scalable production solutions.\nAbility to work directly with customers and technical stakeholders to drive solution design, implementation, and adoption.\nExcellent written and verbal communication skills with engineers, researchers, customers, and executive leadership.\nPREFERRED QUALIFICATIONS:\nExperience training, fine-tuning, or post-training foundation models or open-source LLMs.\nExperience with PyTorch, Hugging Face, JAX, TensorFlow, Ray, vLLM, or distributed AI infrastructure.\nExperience building AI agents, retrieval systems, tool calling, workflow orchestration, or automated code generation.\nExperience with GPU optimization, CUDA, distributed systems, or high-performance computing.\nBackground in forward-deployed engineering, applied AI research, customer engineering, or solutions architecture.\nDemonstrated success delivering AI solutions from customer discovery through deployment with measurable business impact.\nACADEMIC CREDENTIALS:\nBachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, Machine Learning, or a related field (or equivalent practical experience). Master's preferred; PhD is a plus for candidates with strong applied research or systems experience\nLOCATION:\nSanta Clara, CA\n#LI-BW1\nBenefits offered are described: AMD benefits at a glance.\nAMD 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.\nAMD may use Artificial Intelligence to help screen, assess or select applicants for this position. AMD’s “Responsible AI Policy” is available here.\n\nThis posting is for an existing vacancy.\nTHE ROLE:\nWe're looking for a Forward Deployed Research Engineer to build, evaluate, and deploy cutting-edge AI systems that solve complex engineering challenges for enterprise customers.\nThis is not a traditional Solutions Engineer or prompt engineering role. You'll combine deep software engineering, applied AI research, and customer engagement to develop production-ready AI systems using modern LLMs, reinforcement learning, agentic workflows, and post-training techniques.\nTHE PERSON:\nYou'll work directly with customers, researchers, and product teams to transform ambiguous engineering problems into scalable AI solutions. From rapid prototyping to production deployment, you'll help shape both customer success and the evolution of our AI platform.\nWhat Makes This Role Unique\nBuild AI systems that solve real-world engineering problems-not proof-of-concepts.\nWork across applied AI research, software engineering, and customer deployment.\nPartner directly with enterprise engineering teams to define, build, and validate AI solutions.\nInfluence future AI products by translating customer challenges into reusable platform capabilities.\nOwn projects end-to-end-from technical discovery and experimentation through deployment and measurable impact.\nKEY RESPONSIBILITIES:\nPartner with customer engineering teams to understand workflows, technical challenges, and opportunities for AI-driven automation.\nDesign, build, and deploy production-grade AI applications, LLM agents, and engineering automation solutions.\nDevelop evaluation frameworks, benchmarks, testing environments, and data pipelines to measure model quality and business impact.\nBuild and evaluate LLM post-training solutions, including supervised fine-tuning, reinforcement learning, preference optimization, and reward modeling.\nDiagnose and optimize AI system performance across models, data, infrastructure, orchestration, and tooling.\nCollaborate with AI researchers to validate new models and techniques in production environments.\nPresent technical solutions, architecture, and implementation strategies to engineering leaders, customers, and executive stakeholders.\nTransform recurring customer use cases into reusable AI infrastructure, frameworks, and platform capabilities.\nREQUIRED QUALIFICATIONS:\nStrong software engineering experience in Python and at least one systems language such as C++, Rust, C, TypeScript, CUDA, or HIP.\nProven experience building production AI or machine learning systems beyond prompt engineering or API integrations.\nHands-on experience with one or more of the following:LLM post-training\nReinforcement Learning (RLHF, PPO, DPO, GRPO, or similar)\nPreference Optimization\nReward Modeling\nModel or Agent Evaluation\nAI Training or Inference Infrastructure\n\nDeep understanding of transformer-based LLMs, inference, fine-tuning, retrieval, evaluation, and agent architectures.\nExperience designing reproducible evaluation frameworks using benchmarks, testing, and measurable performance metrics.\nStrong systems thinking, debugging, and problem-solving skills.\nExperience translating ambiguous technical requirements into scalable production solutions.\nAbility to work directly with customers and technical stakeholders to drive solution design, implementation, and adoption.\nExcellent written and verbal communication skills with engineers, researchers, customers, and executive leadership.\nPREFERRED QUALIFICATIONS:\nExperience training, fine-tuning, or post-training foundation models or open-source LLMs.\nExperience with PyTorch, Hugging Face, JAX, TensorFlow, Ray, vLLM, or distributed AI infrastructure.\nExperience building AI agents, retrieval systems, tool calling, workflow orchestration, or automated code generation.\nExperience with GPU optimization, CUDA, distributed systems, or high-performance computing.\nBackground in forward-deployed engineering, applied AI research, customer engineering, or solutions architecture.\nDemonstrated success delivering AI solutions from customer discovery through deployment with measurable business impact.\nACADEMIC CREDENTIALS:\nBachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, Machine Learning, or a related field (or equivalent practical experience). Master's preferred; PhD is a plus for candidates with strong applied research or systems experience\nLOCATION:\nSanta Clara, CA\n#LI-BW1\nBenefits offered are described: AMD benefits at a glance.\nAMD 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.\nAMD may use Artificial Intelligence to help screen, assess or select applicants for this position. AMD’s “Responsible AI Policy” is available here.\n\nThis posting is for an existing vacancy.","description_format":"text","description_chars":11391,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":true},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Processors, MCUs & AI Chips","Computer Components","AI Chips & Accelerators"],"lifecycle":[{"event":"open","at":"2026-10-20T09:44:57Z"}],"visa":[],"liveness":{"score":11,"band":"cold","label":"Long shot","p_open":1,"p_active":0.403,"p_room":0.28,"age_days":95,"expected_fill_days":29,"reasons":["conf:1","stale_co","velocity","win:tail","crowd:brand"],"computed_at":"2026-10-26T05:57:25Z"},"pay":null,"html_url":"https://alion.io/job/amd-sr-forward-deployed-ai-engineer","json_url":"https://alion.io/job/amd-sr-forward-deployed-ai-engineer.json","meta":{"generated_at":"2026-10-27T02:31:42Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":1757,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-28T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":93},"rest":"https://alion.io/mcp/rest/get_company?id=93"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Famd-sr-forward-deployed-ai-engineer"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Famd-sr-forward-deployed-ai-engineer"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Famd-sr-forward-deployed-ai-engineer"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/amd-sr-forward-deployed-ai-engineer\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Famd-sr-forward-deployed-ai-engineer"}]}