Stanford University
Machine Learning Research Engineer (1 Year Fixed Term)
Stanford University, Stanford, California, United States, 94305
Overview
Machine Learning Research Engineer (1 Year Fixed Term) – School of Medicine, Stanford, California, United States. The Enigma Project 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. The 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 initiative seeks to offer insights into the algorithms of the brain while serving as a resource for aligning artificial intelligence models with human-like neural representations. We seek exceptional individuals with extensive experience building, using, and fine-tuning large-scale multimodal foundation models. The team will train frontier models on large-scale neural data – multimodal models that relate sensory input to neuronal correlates of perception, action, cognition, and intelligence. Candidates should have expertise in modern deep learning libraries (preferably PyTorch) and developments in multimodal foundation and frontier models. This position offers a collaborative environment at Stanford University in a community renowned for 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 Application
To apply, please send your CV and a one-page interest statement to the stated address (recruiting at enigmaproject dot ai). DESIRED QUALIFICATIONS
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 ML frameworks like TensorFlow or PyTorch Experience with orchestration platforms Experience with cloud computing platforms (e.g., AWS, GCP, Azure) and their ML 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 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 NAS techniques Contributions to open-source ML projects or libraries Education & Experience (REQUIRED)
Bachelor’s degree and three years of relevant experience, or a combination of education and relevant experience. Knowledge, Skills and Abilities (REQUIRED)
• Thorough knowledge of engineering principles 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 up to 10 pounds • Occasionally stand/walk, sit, twist/bend/stoop/squat, grasp forcefully • Rarely kneel/crawl, climb, reach above shoulders, write by hand, sort/file paperwork or parts, operate foot and/or hand controls, lift/carry/push/pull objects heavier than 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 their job. Working Conditions
• May be exposed to high voltage electricity, radiation or electromagnetic fields, lasers, noise, allergens/biohazards/chemicals, confined spaces, heights, temperature extremes, heavy metals, and unusual work hours or overtime. May require travel. The expected pay range for this position is $126,810 to $151,461 annually. Stanford provides pay ranges representing a good faith estimate of compensation. Final pay offered will depend on factors such as scope and responsibilities, qualifications, budget, equity, location, and market. At Stanford, base pay is one aspect of the rewards package. The Cardinal at Work site provides details on benefits and rewards. Details may be discussed during the hiring process. Stanford is an equal employment opportunity and affirmative action employer. All qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other characteristic protected by law. Additional Information
Schedule: Full-time Job Code: 4981 Employee Status: Fixed-Term Grade: J Requisition ID: 106867 Work Arrangement: On Site
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Machine Learning Research Engineer (1 Year Fixed Term) – School of Medicine, Stanford, California, United States. The Enigma Project 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. The 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 initiative seeks to offer insights into the algorithms of the brain while serving as a resource for aligning artificial intelligence models with human-like neural representations. We seek exceptional individuals with extensive experience building, using, and fine-tuning large-scale multimodal foundation models. The team will train frontier models on large-scale neural data – multimodal models that relate sensory input to neuronal correlates of perception, action, cognition, and intelligence. Candidates should have expertise in modern deep learning libraries (preferably PyTorch) and developments in multimodal foundation and frontier models. This position offers a collaborative environment at Stanford University in a community renowned for 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 Application
To apply, please send your CV and a one-page interest statement to the stated address (recruiting at enigmaproject dot ai). DESIRED QUALIFICATIONS
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 ML frameworks like TensorFlow or PyTorch Experience with orchestration platforms Experience with cloud computing platforms (e.g., AWS, GCP, Azure) and their ML 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 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 NAS techniques Contributions to open-source ML projects or libraries Education & Experience (REQUIRED)
Bachelor’s degree and three years of relevant experience, or a combination of education and relevant experience. Knowledge, Skills and Abilities (REQUIRED)
• Thorough knowledge of engineering principles 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 up to 10 pounds • Occasionally stand/walk, sit, twist/bend/stoop/squat, grasp forcefully • Rarely kneel/crawl, climb, reach above shoulders, write by hand, sort/file paperwork or parts, operate foot and/or hand controls, lift/carry/push/pull objects heavier than 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 their job. Working Conditions
• May be exposed to high voltage electricity, radiation or electromagnetic fields, lasers, noise, allergens/biohazards/chemicals, confined spaces, heights, temperature extremes, heavy metals, and unusual work hours or overtime. May require travel. The expected pay range for this position is $126,810 to $151,461 annually. Stanford provides pay ranges representing a good faith estimate of compensation. Final pay offered will depend on factors such as scope and responsibilities, qualifications, budget, equity, location, and market. At Stanford, base pay is one aspect of the rewards package. The Cardinal at Work site provides details on benefits and rewards. Details may be discussed during the hiring process. Stanford is an equal employment opportunity and affirmative action employer. All qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other characteristic protected by law. Additional Information
Schedule: Full-time Job Code: 4981 Employee Status: Fixed-Term Grade: J Requisition ID: 106867 Work Arrangement: On Site
#J-18808-Ljbffr