California Jobs
Machine Learning Systems Engineer (1 Year Fixed Term)
California Jobs, Palo Alto, California, United States, 94306
Overview
Join to apply for the
Machine Learning Systems Engineer (1 Year Fixed Term)
role at
Stanford University .
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 project involves multiple labs and faculty across Stanford, including the Wu Tsai Neurosciences Institute, Stanford Bio-X, and the Human-Centered Artificial Intelligence Institute. The initiative aims to create a functional "digital twin" that captures brain activity at cellular resolution and the intelligent behavior it generates, including perception, motor planning, learning, reasoning, and problem-solving. This position focuses on designing, deploying, and maintaining the compute infrastructure that supports machine learning and data pipeline operations.
Duties Include
Design and develop complex equipment, instruments, or systems; coordinate work phases for components of a major project or a project of moderate scope.
Develop technical and methodological solutions to complex engineering/scientific problems requiring independent analytical thinking.
Develop new or improved equipment, materials, technologies, processes, methods, or software important to the advancement of the field.
Provide technical direction to other research staff, engineering associates, technicians, and/or students as needed.
Contribute to portions of published articles or presentations; draft and prepare scientific papers.
Assist with basic research and development in support of programs/projects; act as advisor/consultant in area of specialty.
Other duties may be assigned.
What We Offer
Collaborative project spanning neuroscience, artificial intelligence, and engineering.
Opportunity to work with a multidisciplinary team dedicated to one mission.
Competitive salary and benefits.
Strong mentoring in career development.
Application In addition to completing the application, please send your CV and a one-page statement of interest to: ...@enigmaproject.ai
Desired Qualifications
3+ years of experience in designing, managing and running large-scale compute infrastructure for machine learning.
Experience with containerization (Docker) and orchestration (Kubernetes or SLURM).
Proficiency in scripting languages such as Python, Bash, or PowerShell.
Strong knowledge of Linux/Unix systems administration.
Ability to work effectively in a collaborative, multidisciplinary environment.
Familiarity with distributed big data tools and pipelines (e.g., Apache Spark, Arrow, Airflow, Delta Lake).
Familiarity with machine learning frameworks (PyTorch or JAX).
Experience with cloud computing resources and GPU-based HPCs for ML.
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 the principles of engineering and related natural sciences.
Demonstrated project management experience.
Certifications & Licenses None
Physical Requirements
Frequent grasping and computer tasks; lift/carry up to 10 pounds.
Occasional standing/walking, sitting, bending, twisting.
Rarely kneeling or climbing; may involve lifting >40 pounds in some tasks.
Working Conditions
May be exposed to electricity, radiation or electromagnetic fields, lasers, noise, allergens/chemicals, confined spaces, extreme temperatures, and other conditions.
May require travel.
The expected pay range for this position is $126,810 to $151,461 annually. Stanford University provides pay ranges as a good faith estimate. Final pay is determined by scope, qualifications, department budget, internal equity, geographic location, and market rates. Benefits information is available on the Cardinal at Work site.
Stanford University 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.
Seniority level
Mid-Senior level
Employment type
Full-time
Job function
Engineering and Information Technology
Industries
Higher Education
#J-18808-Ljbffr
Machine Learning Systems Engineer (1 Year Fixed Term)
role at
Stanford University .
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 project involves multiple labs and faculty across Stanford, including the Wu Tsai Neurosciences Institute, Stanford Bio-X, and the Human-Centered Artificial Intelligence Institute. The initiative aims to create a functional "digital twin" that captures brain activity at cellular resolution and the intelligent behavior it generates, including perception, motor planning, learning, reasoning, and problem-solving. This position focuses on designing, deploying, and maintaining the compute infrastructure that supports machine learning and data pipeline operations.
Duties Include
Design and develop complex equipment, instruments, or systems; coordinate work phases for components of a major project or a project of moderate scope.
Develop technical and methodological solutions to complex engineering/scientific problems requiring independent analytical thinking.
Develop new or improved equipment, materials, technologies, processes, methods, or software important to the advancement of the field.
Provide technical direction to other research staff, engineering associates, technicians, and/or students as needed.
Contribute to portions of published articles or presentations; draft and prepare scientific papers.
Assist with basic research and development in support of programs/projects; act as advisor/consultant in area of specialty.
Other duties may be assigned.
What We Offer
Collaborative project spanning neuroscience, artificial intelligence, and engineering.
Opportunity to work with a multidisciplinary team dedicated to one mission.
Competitive salary and benefits.
Strong mentoring in career development.
Application In addition to completing the application, please send your CV and a one-page statement of interest to: ...@enigmaproject.ai
Desired Qualifications
3+ years of experience in designing, managing and running large-scale compute infrastructure for machine learning.
Experience with containerization (Docker) and orchestration (Kubernetes or SLURM).
Proficiency in scripting languages such as Python, Bash, or PowerShell.
Strong knowledge of Linux/Unix systems administration.
Ability to work effectively in a collaborative, multidisciplinary environment.
Familiarity with distributed big data tools and pipelines (e.g., Apache Spark, Arrow, Airflow, Delta Lake).
Familiarity with machine learning frameworks (PyTorch or JAX).
Experience with cloud computing resources and GPU-based HPCs for ML.
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 the principles of engineering and related natural sciences.
Demonstrated project management experience.
Certifications & Licenses None
Physical Requirements
Frequent grasping and computer tasks; lift/carry up to 10 pounds.
Occasional standing/walking, sitting, bending, twisting.
Rarely kneeling or climbing; may involve lifting >40 pounds in some tasks.
Working Conditions
May be exposed to electricity, radiation or electromagnetic fields, lasers, noise, allergens/chemicals, confined spaces, extreme temperatures, and other conditions.
May require travel.
The expected pay range for this position is $126,810 to $151,461 annually. Stanford University provides pay ranges as a good faith estimate. Final pay is determined by scope, qualifications, department budget, internal equity, geographic location, and market rates. Benefits information is available on the Cardinal at Work site.
Stanford University 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.
Seniority level
Mid-Senior level
Employment type
Full-time
Job function
Engineering and Information Technology
Industries
Higher Education
#J-18808-Ljbffr