{"id":1079970,"url":"https://alion.io/job/applied-materials-ai-materials-research-engineer-4","title":"AI Materials Research Engineer","company":{"id":2749,"name":"Applied Materials","domain":"appliedmaterials.com","url":"https://alion.io/company/applied-materials","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Eightfold","truth_index":{"grade":"A","score":89,"open_postings":504,"ghost_share":0.004,"stale_share":0.216,"repost_share":0.02,"time_to_fill_p50_days":68,"computed_at":"2026-10-01T05:45:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"junior","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":{"min":170000,"max":234000,"currency":"USD","period":"year","gross":null,"usd_annual":234000},"salary_estimate":null,"experience_years_min":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"Hypothesis","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Scikit-learn","optional":false},{"name":"TensorFlow","optional":false},{"name":"HPC","optional":true}],"status":"live","first_seen_at":"2026-08-20T00:00:00Z","employer_posted_date":"2026-08-28","last_verified_at":"2026-10-01T04:47:11Z","board_verified":true,"closed_at":null,"days_open":42,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":42},"description":"Who We Are\nApplied Materials is the global leader in materials science and engineering solutions that are at the foundation of virtually every new semiconductor chip and advanced display in the world. The equipment that we create and service is essential to advancing AI and accelerating the commercialization of next-generation semiconductor chips. Join us and push the boundaries of materials science and engineering in a company at the foundation of the electronics industry. The work we do together advances the world’s technology.\nWhat We Offer\nSalary:\n$170,000.00 - $234,000.00Location:\nSanta Clara,CAYou’ll benefit from a supportive work culture that encourages you to learn, develop, and grow your career as you take on challenges and drive innovative solutions for our customers. We empower our team to push the boundaries of what is possible-while learning every day in a supportive leading global company. Visit our Careers website to learn more.\nAt Applied Materials, we care about the health and wellbeing of our employees. We’re committed to providing programs and support that encourage personal and professional growth and care for you at work, at home, or wherever you may go. Learn more about our benefits.\nRole Summary\nApplied Materials is seeking an AI MaterialsResearch Engineer to accelerate semiconductor materials discovery using Scientific AI, Computational MaterialsScience, and Machine Learning. The role combines materials science expertise with AI/ML, simulation, and data-driven modeling to develop next-generation materials and process innovations. Based on related internal Materials AI role descriptions.\nKey Responsibilities\nDevelop AI/ML models for:Materials property prediction\nMaterials screening and optimization\nProcess-performance modeling\nGenerative materials design\n\nApply computational materialsmethodologies including:Density Functional Theory (DFT)\nMolecular Dynamics (MD)\nKinetic Monte Carlo (kMC)\nPhase-field and Monte Carlo simulations\n\nBuild AI surrogate models to accelerate simulation-driven research.\nCreate materials informatics pipelines integrating:Experimental data\nCharacterization results\nSimulation outputs\nScientific literature\n\nDevelop AI copilots and agentic workflows for:Literature review\nHypothesis generation\nExperiment planning\nSimulation orchestration\n\nCollaborate with materials scientists, process engineers, and AI teams to deliver Scientific AI solutions. \nRequired Qualifications\nMS/PhD in Materials Science, Computational Materials Science, Physics, Chemical Engineering, or related field.\n2-5 years of experience in Computational Materials Science, Materials Informatics, Scientific ML, or AI for scientific applications.\nStrong Python programming and ML experience (PyTorch, TensorFlow, Scikit-Learn).\nExperience with one or more computational methods:DFT\nMD\nkMC\nPhase-Field Modeling\n\nStrong understanding of:Crystal structures\nThermodynamics\nKinetics\nDefect physics\nSemiconductor materials\n\nPreferred Qualifications\nExperience with simulation platforms such as VASP, Quantum Espresso, CP2K, LAMMPS, or GROMACS.\nExperience with Materials Project, OQMD, NOMAD, or similar databases.\nFamiliarity with:Graph Neural Networks (GNNs)\nMaterials Foundation Models\nPhysics-Informed ML\nGenerative AI for materials design\n\nExperience using cloud/HPC environments for large-scale model training and simulations.\nAdditional Information\nTime Type:\nFull timeEmployee Type:\nAssignee / RegularTravel:\nNot SpecifiedRelocation Eligible:\nNoThe salary offered to a selected candidate will be based on multiple factors including location, hire grade, job-related knowledge, skills, experience, and with consideration of internal equity of our current team members. In addition to a comprehensive benefits package, candidates may be eligible for other forms of compensation such as participation in a bonus and a stock award program, as applicable.\nFor all sales roles, the posted salary range is the Target Total Cash (TTC) range for the role, which is the sum of base salary and target bonus amount at 100% goal achievement.\nApplied Materials is an Equal Opportunity Employer. Qualified applicants will receive consideration for employment without regard to race, color, national origin, citizenship, ancestry, religion, creed, sex, sexual orientation, gender identity, age, disability, veteran or military status, or any other basis prohibited by law.\nIn addition, Applied endeavors to make our careers site accessible to all users. If you would like to contact us regarding accessibility of our website or need assistance completing the application process, please contact us via e-mail at ,or by calling our HR Direct Help Line at 877-612-7547, option 1, and following the prompts to speak to an HR Advisor. This contact is for accommodation requests only and cannot be used to inquire about the status of applications.","description_format":"text","description_chars":4908,"description_truncated":false,"requirements":{"experience_years_min":2,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"master","optional":false},"security_clearance":false,"languages":[]},"benefits":["Equity"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":true,"industries":["Semiconductor Equipment"],"lifecycle":[{"event":"open","at":"2026-09-20T18:11:59Z"}],"liveness":{"score":52,"band":"ok","label":"Likely open","p_open":1,"p_active":0.724,"p_room":0.72,"age_days":42,"expected_fill_days":68,"reasons":["conf:0","velocity","win:mid","crowd:junior,brand"],"computed_at":"2026-10-01T05:45:00Z"},"pay":{"stated_usd_annual":234000,"is_top_pay":false},"html_url":"https://alion.io/job/applied-materials-ai-materials-research-engineer-4","json_url":"https://alion.io/job/applied-materials-ai-materials-research-engineer-4.json","meta":{"generated_at":"2026-10-01T20:39:53Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":3097,"day_limit":5000,"remaining_today":1903,"minute_limit":60,"resets_at":"2026-10-02T00:00:00Z"}}}