{"id":3360676,"url":"https://alion.io/job/asml-ai-research-and-development-engineer","title":"AI Research and Development Engineer","company":{"id":17151,"name":"ASML","domain":"asml.com","url":"https://alion.io/company/asml","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":82,"open_postings":115,"ghost_share":0,"stale_share":0.904,"repost_share":0,"time_to_fill_p50_days":16,"computed_at":"2026-10-30T05:48:23Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["San Jose, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":162750,"max":238700,"currency":"USD","period":"year","gross":null,"usd_annual":238700},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Fine-tuning","optional":false},{"name":"Hallucination","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Multimodal AI","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"RAG","optional":false},{"name":"SFT","optional":false},{"name":"Synthetic Data","optional":false},{"name":"Tokenization","optional":false},{"name":"VLM","optional":false},{"name":"Electron Microscopy (SEM/TEM)","optional":true},{"name":"LoRA","optional":true},{"name":"Multi-Agent Systems","optional":true},{"name":"PEFT","optional":true},{"name":"QLoRA","optional":true},{"name":"Quantization","optional":true},{"name":"Reinforcement Learning","optional":true}],"status":"live","first_seen_at":"2026-10-27T21:15:38Z","employer_posted_date":"2026-10-27","last_verified_at":"2026-10-30T02:00:58Z","board_verified":true,"closed_at":null,"days_open":2,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":2},"description":"Position Overview\nWe are seeking talented and motivated AI Research and Development Engineers to join our team at ASML, working at the intersection of advanced artificial intelligence and semiconductor inspection technologies.\nThe primary requirement for this position is hands-on experience training or fine-tuning LLMs and/or VLMs across the end-to-end model development lifecycle, including data preparation, model adaptation, training, evaluation, performance optimization, and deployment or inference.\nThis research-focused role involves developing advanced LLM/VLM capabilities and translating research concepts into functional prototypes for real-world engineering applications. Experience developing Agentic AI systems is strongly preferred and will be considered an important differentiator. Semiconductor inspection or SEM experience is beneficial but not required, as domain knowledge can be developed through collaboration with internal experts.\nKey Responsibilities\nOwn end-to-end LLM/VLM development workflows, including data curation and preprocessing, model selection, training or fine-tuning, evaluation, inference optimization, deployment, and iterative improvement.\nDesign and execute model adaptation strategies such as supervised fine-tuning, instruction tuning, parameter-efficient fine-tuning, preference optimization, and continued pretraining, as appropriate for the use case.\nBuild and maintain high-quality training and evaluation datasets, including data cleaning, labeling strategies, synthetic-data generation, quality checks, and contamination controls.\nEstablish rigorous evaluation and benchmarking frameworks covering model quality, task performance, robustness, hallucination, safety, latency, throughput, and cost.\nDevelop innovative Agentic AI solutions that integrate trained or tuned models with tools, planning, memory, and workflow orchestration.\nApply advanced LLM, VLM, multimodal AI, machine learning, and deep learning techniques to semiconductor inspection and other complex engineering applications.\nCollaborate with cross-functional teams and customers to identify research opportunities, translate engineering requirements into model-development objectives, and validate emerging technologies.\nSupport the transition of validated AI research and prototypes into reusable platforms and potential product applications.\nRequired Qualifications\nMaster’s or PhD degree in Computer Science, Artificial Intelligence, Machine Learning, Electrical Engineering, or a related field; equivalent practical experience may also be considered.\nDemonstrated hands-on experience training or fine-tuning LLMs and/or VLMs end to end, with direct ownership of data preparation, training execution, evaluation, performance optimization, and deployment or inference.Practical experience with modern deep-learning frameworks and model-development tooling, especially Python and PyTorch.\nStrong understanding of transformer-based models, tokenization, optimization, training dynamics, evaluation methods, and common model failure modes.\n\nExperience working with distributed training or multi-GPU environments and diagnosing training issues such as instability, overfitting, data-quality problems, and performance regressions.\nAbility to design meaningful experiments, interpret results, and make evidence-based trade-offs across model architecture, training data, model quality, compute requirements, latency, and cost.\nStrong programming skills with the ability to independently design, implement, test, and evaluate AI algorithms and prototypes.\nExcellent analytical thinking, independent problem-solving, and technical reasoning skills.\nStrong teamwork, adaptability, and ability to thrive in a fast-paced research and development environment.\nExcellent communication and presentation skills, with the ability to clearly articulate complex technical concepts and research findings.\nCandidates will be evaluated primarily on demonstrated end-to-end LLM/VLM training and tuning accomplishments, technical depth, and research capabilities rather than years of professional experience. Experience limited to prompt engineering, RAG implementation, or hosted-model API integration alone does not satisfy the primary model-training requirement.\nPreferred Qualifications\nStrongly preferred: Experience developing Agentic AI systems, including tool-using agents, planning, memory, multi-agent systems, agent orchestration, and intelligent workflows.\nExperience with LLM/VLM adaptation and alignment techniques such as LoRA or QLoRA, supervised fine-tuning, preference optimization, reinforcement learning, or related methods.\nExperience with LLM/VLM data pipelines, synthetic-data generation, experiment tracking, model registries, distributed training, optimized inference, quantization, or model serving.\nExperience evaluating LLM/VLM systems for factuality, robustness, safety, latency, throughput, and cost in real application workflows.\nAdditional plus: Knowledge of semiconductor manufacturing, voltage-contrast inspection, scanning electron microscopy, e-beam inspection, or defect analysis. Prior SEM experience is not required.\nWhy Join Us?\nCutting-edge innovation: Train, tune, and evaluate next-generation LLM/VLM technologies for advanced engineering applications.\nResearch with real-world impact: Develop model capabilities and Agentic AI solutions with opportunities to influence future products.\nEnd-to-end ownership: Work across data preparation, model training, evaluation, optimization, deployment, and application integration.\nDynamic and collaborative environment: Enjoy the agility and innovative spirit of a startup-like team within a global technology leader.\nProfessional growth: Work on challenging multidisciplinary problems and continuously expand your technical expertise.\nTravel Requirements\nBusiness travel may be required as needed.\nThe current base annual salary range for this role is currently:\n$162,750-238,700Pay scales are determined by role, level, location and alignment with market data. Individual pay is determined through interviews and an assessment of several factors that that are unique to each candidate, including but not limited to job-related skills, relevant education and experience, certifications, abilities of the candidate and pay relative to other team members.\nThe Company offers employees and their families, medical, dental, vision, and basic life insurance. Employees are able to participate in the Company’s 401k plan. Employees will also receive eight (8) hours of vacation leave every month and (13) paid holidays throughout the calendar year. For more information, please contact the Recruiter or click on this link Compensation & Benefits in the US.\nAll new ASML jobs have a minimum application deadline of 10 days.\nInclusion and diversity\nASML is an Equal Opportunity Employer that values and respects the importance of a diverse and inclusive workforce. It is the policy of the company to recruit, hire, train and promote persons in all job titles without regard to race, color, religion, sex, age, national origin, veteran status, disability, sexual orientation, or gender identity. We recognize that inclusion and diversity is a driving force in the success of our company.\nNeed to know more about applying for a job at ASML? Read our frequently asked questions.\nRequest an Accommodation\nASML provides reasonable accommodations to applicants for ASML employment and ASML employees with disabilities. An accommodation is a change in work rules, facilities, or conditions which enable an individual with a disability to apply for a job, perform the essential functions of a job, and/or enjoy equal access to the benefits and privileges of employment. If you are in need of an accommodation to complete an application, participate in an interview, or otherwise participate in the employee pre-selection process, please send an email to  to initiate the company’s reasonable accommodation process.\nPlease note: This email address is solely intended to provide a method for applicants to initiate ASML’s process to request accommodation(s). 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