Join to apply for the Machine Learning Systems Engineer (1 Year Fixed Term) role at Stanford University
Join to apply for the Machine Learning Systems Engineer (1 Year Fixed Term) role at Stanford University
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The Department of Ophthalmology in the School of Medicine at Stanford University is launching an interdisciplinary Neuro-AI project dedicated to building a foundation model of the brain. This endeavor will involve multiple labs and faculty across the Stanford campus, including the Wu Tsai Neurosciences Institute, Stanford Bio-X, and the Human-Centered Artificial Intelligence Institute. Leveraging cutting-edge advances in electrophysiology and machine learning, this project aims to create a functional "digital twin" — a model that captures both the activity dynamics of the brain at cellular resolution and the intelligent behavior it generates, including perception, motor planning, learning, reasoning, and problem-solving.
This ambitious initiative promises to offer unprecedented insights into the brain's algorithms of perception and cognition while serving as a key resource for aligning artificial intelligence models with human-like neural representations. As part of this project, we are seeking talented systems engineers with extensive experience in large scale data and compute clusters. As a Systems Engineer, you will be responsible for designing, deploying, and maintaining the compute infrastructure that supports our machine learning and data pipeline operations.
This position promises a vibrant and cooperative atmosphere within the laboratories of Andreas Tolias (https://toliaslab.org), Tirin Moore (https://www.moorelabstanford.com) and other labs at Stanford University renowned for their expertise in perception, cognition, pioneering neural recording techniques, computational neuroscience, machine learning, and Neuro-AI research.
Duties Include
Design and develop complex and specialized equipment, instruments, or systems; coordinate detailed phases of work related to responsibility for part of a major project or for an entire project of moderate scope.Develop technical and methodological solutions to complex engineering/scientific problems requiring independent analytical thinking and advanced knowledge.Develop creative new or improved equipment, materials, technologies, processes, methods, or software important to the advancement of the field.Contribute technical expertise, and perform basic research and development in support of programs/projects; act as advisor/consultant in area of specialty.Contribute to portions of published articles or presentations; prepare and write reports; draft and prepare scientific papers.Provide technical direction to other research staff, engineering associates, technicians, and/or students, as needed.* - Other duties may also be assigned
What We Offer
Work on a collaborative and uniquely positioned project spanning several disciplines, from neuroscience to artificial intelligence and engineering.Work jointly with a vibrant team of researchers and scientists in a project dedicated to one mission, rooted in academia but inspired by science in industry.Competitive salary and benefits.Strong mentoring in career development.
Application
In addition to completing the application, please send your CV and one page interest statement to: recruiting@enigmaproject.ai
Desired Qualifications
3+ years of experience in designing, managing and running large-scale compute infrastructure in the context of machine learningExperience with containerization technologies like Docker and orchestration platforms like Kubernetes or SLURMProficiency in scripting languages such as Python, Bash, or PowerShellStrong knowledge of Linux/Unix systems administrationAbility to work effectively in a collaborative, multidisciplinary environmentFamiliarity with modern distributed big data tools and pipelines such as Apache Spark, Arrow, Airflow, Delta Lake, or similarFamiliarity with machine learning frameworks like PyTorch or JAXIn-depth experience with cloud computing resourcesThorough knowledge of GPU-based HPCs in the context of machine learning.
Education & Experience (required)
Bachelor's degree and three years of relevant experience, or combination of education and relevant experience.
Knowledge, Skills And Abilities (required)
Thorough knowledge of the principles of engineering and related natural sciences.Demonstrated project management experience.
Certifications & Licenses
None
PHYSICAL REQUIREMENTS*:
Frequently grasp lightly/fine manipulation, perform desk-based computer tasks, lift/carry/push/pull objects that weigh up to 10 pounds.Occasionally stand/walk, sit, twist/bend/stoop/squat, grasp forcefully.Rarely kneel/crawl, climb (ladders, scaffolds, or other), reach/work above shoulders, use a telephone, writing by hand, sort/file paperwork or parts, operate foot and/or hand controls, lift/carry/push/pull objects that weigh >40 pounds.- Consistent with its obligations under the law, the University will provide reasonable accommodation to any employee with a disability who requires accommodation to perform the essential functions of his or her job.
Working Conditions
May be exposed to high voltage electricity, radiation or electromagnetic fields, lasers, noise > 80dB TWA, Allergens/Biohazards/Chemicals /Asbestos, confined spaces, working at heights ?10 feet, temperature extremes, heavy metals, unusual work hours or routine overtime and/or inclement weather.May require travel.
The expected pay range for this position is $126,810 to $151,461 annually.
Stanford University provides pay ranges representing its good faith estimate of what the university reasonably expects to pay for a position. The pay offered to a selected candidate will be determined based on factors such as (but not limited to) the scope and responsibilities of the position, the qualifications of the selected candidate, departmental budget availability, internal equity, geographic location and external market pay for comparable jobs.
At Stanford University, base pay represents only one aspect of the comprehensive rewards package. The Cardinal at Work website (https://cardinalatwork.stanford.edu/benefits-rewards) provides detailed information on Stanford’s extensive range of benefits and rewards offered to employees. Specifics about the rewards package for this position may be discussed during the hiring process.
Consistent with its obligations under the law, the University will provide reasonable accommodations to applicants and employees with disabilities. Applicants requiring reasonable accommodation for any part of the application or hiring process should contact Stanford University Human Resources by submitting a contact form.
Stanford is an equal employment opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law.
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#J-18808-Ljbffr Read LessThank you for your interest in Stanford University.While we have instituted a hiring pause for non-critical staff positions, we are actively recruiting for most of the positions currently listed on our careers page.We will update the page when the broader hiring pause is lifted.
Job Summary
DATE POSTED 2 days agoSchedule Full-timeJob Code 4981Employee Status Fixed-TermRequisition ID 106866Work Arrangement On SiteThe Enigma Project (enigmaproject.ai ) is a research organization based in the Department of Ophthalmology at Stanford University School of Medicine, dedicated to understanding the computational principles of natural intelligence using the tools of artificial intelligence. Leveraging recent advances in neurotechnology and machine learning, this project aims to create a foundation model of the brain, capturing the relationship between perception, cognition, behavior, and the activity dynamics of the brain. This ambitious initiative promises to offer unprecedented insights into the algorithms of the brain while serving as a key resource for aligning artificial intelligence models with human-like neural representations.
As part of this project, we seek exceptional individuals with extensive experience building, using, and fine-tuning large-scale multimodal foundation models. The team will be responsible for training frontier models on large-scale data of neuronal recordings - multimodal models, i.e., digital twins of a primate brain, that can relate unprecedented amounts of sensory input to neuronal correlates of perception, action, cognition, and intelligence. We expect the candidate to have expertise in modern deep learning libraries (preferably PyTorch) and recent developments in multimodal foundation and frontier models. This position promises a vibrant atmosphere at Stanford University in a collaborative community renowned for expertise in computational neuroscience and deep learning.
Role & Responsibilities:
• Implement and optimize the latest machine learning algorithms/models to train multimodal foundation models on neural data
• Develop and maintain scalable, efficient, and reproducible machine-learning pipelines
• Conduct large-scale ML experiments, using the latest MLOps platforms
• Run large-scale distributed model training on high-performance computing clusters or cloud platforms
• Collaborate with machine learning researchers, data scientists, and systems engineers to ensure seamless integration of models and infrastructure
• Monitor and optimize model performance, resource utilization, and cost-effectiveness
• Stay up-to-date with the latest advancements in machine learning tools, frameworks, and methodologies
• * - Other duties may also be assigned
What we offer:
• An environment in which to pursue fundamental research questions in AI and neuroscience
• A vibrant team of engineers and scientists in a project dedicated to one mission, rooted in academia but inspired by science in industry.
• Access to unique datasets spanning artificial and biological neural networks
• State-of-the-art computing infrastructure
• Competitive salary and benefits package
• Collaborative environment at the intersection of multiple disciplines
• Location at Stanford University with access to its world-class research community
• Strong mentoring in career development.
Key qualifications:
Master's degree in Computer Science or related field with 2+ years of relevant industry experience, OR Bachelor's degree with 4+ years of relevant industry experience
2+ years of practical experience in implementing and optimizing machine learning algorithms with distributed training using common libraries (e.g. Ray, DeepSpeed, HF Accelerate, FSDP)
Strong programming skills in Python, with expertise in machine learning frameworks like TensorFlow or PyTorch
Experience with orchestration platforms
Experience with cloud computing platforms (e.g., AWS, GCP, Azure) and their machine learning services
Familiarity with MLOps platforms (e.g. MLflow, Weights & Biases)
Strong understanding of software engineering best practices, including version control, testing, and documentation
Preferred qualifications:
Familiarity with training, fine tuning, and quantization of LLMs or multimodal models using common techniques and frameworks (LoRA, PEFT, AWQ, GPTQ, or similar)
Familiarity with modern big data tools and pipelines such as Apache Spark, Arrow, Airflow, Delta Lake, or similar
Experience with AutoML and Neural Architecture Search (NAS) techniques
Contributions to open-source machine learning projects or libraries
EDUCATION & EXPERIENCE (REQUIRED):
Bachelor's degree and three years of relevant experience, or combination of education and relevant experience.
KNOWLEDGE, SKILLS AND ABILITIES (REQUIRED):
• Thorough knowledge of the principles of engineering and related natural sciences.
• Demonstrated project management experience.
CERTIFICATIONS & LICENSES:
None
PHYSICAL REQUIREMENTS*:
• Frequently grasp lightly/fine manipulation, perform desk-based computer tasks, lift/carry/push/pull objects that weigh up to 10 pounds.
• Occasionally stand/walk, sit, twist/bend/stoop/squat, grasp forcefully.
• Rarely kneel/crawl, climb (ladders, scaffolds, or other), reach/work above shoulders, use a telephone, writing by hand, sort/file paperwork or parts, operate foot and/or hand controls, lift/carry/push/pull objects that weigh >40 pounds.
* - Consistent with its obligations under the law, the University will provide reasonable accommodation to any employee with a disability who requires accommodation to perform the essential functions of his or her job.
WORKING CONDITIONS:
• May be exposed to high voltage electricity, radiation or electromagnetic fields, lasers, noise > 80dB TWA, Allergens/Biohazards/Chemicals /Asbestos, confined spaces, working at heights ?10 feet, temperature extremes, heavy metals, unusual work hours or routine overtime and/or inclement weather.
• May require travel.
The expected pay range for this position is $126,810 to $151,461 annually.
Stanford University provides pay ranges representing its good faith estimate of what the university reasonably expects to pay for a position. The pay offered to a selected candidate will be determined based on factors such as (but not limited to) the scope and responsibilities of the position, the qualifications of the selected candidate, departmental budget availability, internal equity, geographic location and external market pay for comparable jobs.
At Stanford University, base pay represents only one aspect of the comprehensive rewards package. The Cardinal at Work website ( https://cardinalatwork.stanford.edu/benefits-rewards ) provides detailed information on Stanford’s extensive range of benefits and rewards offered to employees. Specifics about the rewards package for this position may be discussed during the hiring process.
Consistent with its obligations under the law, the University will provide reasonable accommodations to applicants and employees with disabilities. Applicants requiring reasonable accommodation for any part of the application or hiring process should contact Stanford University Human Resources by submitting a contact form .
Stanford is an equal employment opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law.
School of Medicine, Stanford, California, United States
School of Medicine, Stanford, California, United States
We're always looking for people who can bring new perspectives and life experiences to our team. Found the perfect role and ready to apply? Learn more on what to expect next.
#J-18808-Ljbffr Read LessThe Department of Obstetrics and Gynecology at Stanford University seeks an exceptional physician leader for a full-time faculty position as Chief of the Division of Gynecology and Gynecologic Specialties, at the rank of Associate Professor or Professor in the University Medical Line (UML) or Clinician Educator Line (CE). The Division is seeking a leader for our dynamic team of over 30+ faculty members and 5 Advanced Practice Providers in 5 specialty sections. We are seeking a person who combines proven leadership skills in team building, program development and process improvement. The ideal candidate will have a record of outstanding academic accomplishment in gynecology or a gynecologic sub-specialty, possess advanced clinical and/or surgical skill sets, and be dedicated to excellence in clinical care, clinic operations, teaching, and/or research, and have the creative vision to help shape the future of a dynamic, growing, and progressive division. The Chief of Gynecology and Gynecologic Specialties will play a crucial role in representing the service line on the Stanford Health Care Ambulatory Leadership Team and will work closely with the Department Chair and leadership to strategically grow and enhance our services.
Stanford offers a wealth of academic opportunities, including basic, translational, and clinical research programs. Our division includes several specialized sections: Academic Specialists in Obstetrics and Gynecology, Complex Family Planning, Minimally Invasive Surgery, Pediatric and Adolescent Gynecology, and Urogynecology. We are committed to innovative programs, including the Menopause and Healthy Aging initiative and LGBTQ+ health services. Our division features pioneering services such as the Stanford Fibroid Center, a collaborative effort with Interventional Radiology, and the Pelvic Health Center, a comprehensive multidisciplinary program. We are a busy service line operating across two hospital systems, managing over 30,000 patient visits annually (with approximately one-third being new patients) and performing over 1,800 surgical cases. We also provide innovative medical education initiatives, including fellowships in Complex Family Planning, Urogynecology (in partnership with Urology), and Pediatric and Adolescent Gynecology.
The major criteria for appointment for faculty in the University Medical Line shall be excellence in the overall mix of clinical care, clinical teaching, scholarly activity that advances clinical medicine, and institutional service appropriate to the programmatic need the individual is expected to fulfill. The major criterion for appointment as Clinician Educators is excellence in the overall mix of clinical care, teaching, administrative and/or scholarship appropriate to the programmatic need the individual is expected to fulfill. Candidates should have an MD, DO or equivalent and be board certified in Obstetrics and Gynecology by the American Board of Obstetrics & Gynecology. Faculty rank and line will be determined by the qualifications and experience of the successful candidate.
Stanford is located in Silicon Valley, the heart of the Bay Area bioscience community, and is a friendly and collegial place to work. Opportunities for collaboration with the tech sector and for innovation abound. The surrounding communities of San Francisco and the greater Bay Area offer an unrivaled array of recreational and cultural venues with a temperate climate that allows for year-round enjoyment.
Stanford is an equal employment opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law. Stanford welcomes applications from all who would bring additional dimensions to the University's research, teaching and clinical missions.
Consistent with its obligations under the law, the University will provide reasonable accommodations to applicants and employees with disabilities. Applicants requiring a reasonable accommodation for any part of the application or hiring process should contact disability.access@stanford.edu .
The university's central functions of research and education depend on freedom of thought, and expression. The Department of Obstetrics and Gynecology, School of Medicine, and Stanford University value faculty who will help foster an open and respectful academic environment for colleagues, students, and staff with a wide range of backgrounds, identities, and perspectives. Candidates may choose to include as part of their research and teaching statements a brief discussion about how their work and experience will further these values.
Salary Range:
The expected base pay range for this position is:
Associate Professor $ 317,000 - $335,000
Professor $362,000 – $386,000
This pay range reflects base pay, which is based on faculty rank and years in rank. It does not include all components of the School of Medicine's faculty compensation program or pay from participation in departmental incentive compensation programs. For more information about compensation and our wide-range of benefits, including housing assistance, please contact the hiring department.
Stanford University has provided a pay range representing its good faith estimate of what the university reasonably expects to pay for the position. The pay offered to the selected candidate will be determined based on factors including (but not limited to) the experience and qualifications of the selected candidate including equivalent years in rank, training, and field or discipline; internal equity; and external market pay for comparable jobs.
Applications will be accepted beginning July 17, 2025, and will be continue until a finalist has been identified. Interested candidates should apply via: https://facultypositions.stanford.edu/en-us/job/494866/division-chief-gynecologic-and-gynecologic-specialtiesstanford-gynecology-service and include a copy of their curriculum vitae, a brief letter outlining their interests and names of three references.
Candidates may contact the Search Committee Chair, Dr. Yasser El-Sayed, c/o Cathy Seckel, cseckel@stanford.edu with any additional questions.
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As the inaugural head of Stanford’s new Office of Investigations (OI), the Executive Director will oversee a team of investigators responsible for conducting independent and neutral fact finding on a variety of subject matters involving students, faculty and staff. The Executive Director will provide strategic leadership and management, overseeing investigations performed by other OI investigators and ensuringtimely completion and adherence with applicable University and legal requirements. In addition, theExecutive Director will personally perform investigative functions as needed.
Core Responsibilities:
Develop and implement a strategic vision and plan for University investigations in accordance with industry best practices; set long range direction and establish policies, procedures, templates and trainings.Coordinate with campus partners to designate investigators and ensure the timely completion of thorough, neutral and fair investigations.Serve as the lead investigator as needed and engage in fact finding activities, including but not limited to, conducting intakes, identifying relevant laws and policies, interviewing parties and witnesses, collecting and reviewing relevant documentary evidence, assessing the sufficiency andThe job duties listed are typical examples of work performed by positions in this job classification and are not designed to contain or be interpreted as a comprehensive inventory of all duties, tasks, and responsibilities. Specific duties and responsibilities may vary depending on department or program needs without changing the general nature and scope of the job or level of responsibility. Employees may also perform other duties as assigned.
The expected salary range is $250,000 to $330,000 per annum.
Stanford University provides pay ranges representing its good faith estimate of what the University reasonably expects to pay for a position. The pay offered to a selected candidate will be determined based on factors such as (but not limited to) the scope and responsibilities of the position, the qualifications of the selected candidate, departmental budget availability, internal equity, geographic location and external market pay for comparable jobs.
At Stanford University, base pay represents only one aspect of the comprehensive rewards package. The Cardinal at Work website (https://cardinalatwork.stanford.edu/benefits-rewards) provides detailed information on Stanford’s extensive range of benefits and rewards offered to employees. Specifics about the rewards package for this position may be discussed during the hiring process.
The final candidate will need to successfully pass a background check to be considered for this position.
Consistent with its obligations under the law, the University will provide reasonable accommodation to any employee with a disability who requires accommodation to perform the essential functions of their job.
Stanford is an equal employment opportunity and affirmative action employer. All qualified applicants will receive consideration for employment regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law.
Stanford University has exclusively retained Major, Lindsey & Africa to conduct a search for this position. Interested candidates should submit a resume addressed to:
Heather Fine, Partner: hfine@mlaglobal.com
Office of the General Counsel, Stanford, California, United States
Office of the General Counsel, Stanford, California, United States
Office of the General Counsel, Stanford, California, United States
#J-18808-Ljbffr Read Less