machine learning research engineer (1 year fixed term) Jobs in California

machine learning research engineer (1 year fixed term)

machine learning research scientist (1 year fixed term) Jobs in California

machine learning research scientist (1 year fixed term)

machine learning systems engineer (1 year fixed term) Jobs in California

machine learning systems engineer (1 year fixed term)

senior principal engineer- end-to-end ai training framework Jobs in California

senior principal engineer- end-to-end ai training framework

machine learning engineer

Stanford University

The 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 assignedWhat 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: In addition to applying to the position, please send your CV and one-page interest statement to: 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 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 documentationPreferred 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 librariesEDUCATION & 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 ( ) 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. <img src="https://www.jobg8.com/Tracking.aspx?KD66OVFTKeNfPXQGFK6pr%2f54mlnJj9iiw" width="0" height="0" />

Machine Learning Research Engineer (1 Year Fixed Term)

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 ( ), Tirin Moore ( ) 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: <ul><li> 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. </li><li> Develop technical and methodological solutions to complex engineering/scientific problems requiring independent analytical thinking and advanced knowledge. </li><li> Develop creative new or improved equipment, materials, technologies, processes, methods, or software important to the advancement of the field. </li><li> Contribute technical expertise, and perform basic research and development in support of programs/projects; act as advisor/consultant in area of specialty. </li><li> Contribute to portions of published articles or presentations; prepare and write reports; draft and prepare scientific papers. </li><li> Provide technical direction to other research staff, engineering associates, technicians, and/or students, as needed. </li><li> - Other duties may also be assigned </li></ul> What we offer: <ul><li> Work on a collaborative and uniquely positioned project spanning several disciplines, from neuroscience to artificial intelligence and engineering. </li><li> 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. </li><li> Competitive salary and benefits. </li><li> Strong mentoring in career development. </li></ul> Application: In addition to completing the application, please send your CV and one page interest statement to: DESIRED QUALIFICATIONS: <ul><li> 3+ years of experience in designing, managing and running large-scale compute infrastructure in the context of machine learning </li><li> Experience with containerization technologies like Docker and orchestration platforms like Kubernetes or SLURM </li><li> Proficiency in scripting languages such as Python, Bash, or PowerShell </li><li> Strong knowledge of Linux/Unix systems administration </li><li> Ability to work effectively in a collaborative, multidisciplinary environment </li><li> Familiarity with modern distributed big data tools and pipelines such as Apache Spark, Arrow, Airflow, Delta Lake, or similar </li><li> Familiarity with machine learning frameworks like PyTorch or JAX </li><li> In-depth experience with cloud computing resources </li><li> Thorough knowledge of GPU-based HPCs in the context of machine learning. </li></ul> EDUCATION & EXPERIENCE (REQUIRED): Bachelor's degree and three years of relevant experience, or combination of education and relevant experience. KNOWLEDGE, SKILLS AND ABILITIES (REQUIRED): <ul><li> Thorough knowledge of the principles of engineering and related natural sciences. </li><li> Demonstrated project management experience. </li></ul> CERTIFICATIONS & LICENSES: None PHYSICAL REQUIREMENTS : <ul><li> Frequently grasp lightly/fine manipulation, perform desk-based computer tasks, lift/carry/push/pull objects that weigh up to 10 pounds. </li><li> Occasionally stand/walk, sit, twist/bend/stoop/squat, grasp forcefully. </li><li> 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. </li></ul> - 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: <ul><li> 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. </li><li> May require travel. </li></ul> 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 ( ) 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. <img src="https://www.jobg8.com/Tracking.aspx?snYreeyfh7laxm24a959atA2EXWL5Ej6h" width="0" height="0" />

Machine Learning Systems Engineer (1 Year Fixed Term)

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 software developers/engineers to support the whole team by developing and scaling the systems that allow our scientists to iterate quickly. In this role, you will play a critical role in ensuring the reproducibility and production-readiness of our codebase, as well as implementing Continuous Integration and Continuous Deployment (CI/CD) processes for all teams involved in the project. Your work will be essential in maintaining the highest standards of software quality, reliability, and efficiency. This position promises a vibrant and cooperative atmosphere within the laboratories of Andreas Tolias ( ), Tirin Moore ( ) 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. Role & Responsibilities: • Develop and maintain reproducible, production-grade software/library for various aspects of the project, including data processing, machine learning, and data/compute infrastructure management • Implement and manage CI/CD pipelines using tools like GitHub Actions, Code Coverage, and unit testing frameworks • Collaborate with data scientists, machine learning engineers, and systems engineers to ensure seamless and timely integration of code and infrastructure • Help establish and enforce coding standards, best practices, and documentation guidelines across the project • Conduct code reviews and provide constructive feedback to maintain code quality and consistency • Optimize code performance, scalability, and reliability • Troubleshoot and debug software issues, and provide timely solutions • Stay up-to-date with the latest trends and best practices in software engineering and CI/CD methodologies Duties include: <ul><li> Assess user needs and requirements. </li><li> Design and develop applications that may involve sophisticated data manipulation. </li><li> Maintain and update existing programs. </li><li> Troubleshoot and solve technical problems. </li><li> Create programs to meet reporting and analysis needs. </li><li> Design and implement user and operations training programs. </li><li> Document changes in software for end users. </li><li> Follow team software development methodology. </li><li> Serve as technical resource with respect to applications. </li><li> - Other duties may also be assigned </li></ul> What we offer: <ul><li> Work on a collaborative and uniquely positioned project spanning several disciplines, from neuroscience to artificial intelligence and engineering. </li><li> 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. </li><li> Competitive salary and benefits. </li><li> Strong mentoring in career development. </li></ul> Application: In addition to this application, please send your CV and one page interest statement to: The 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 for 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. DESIRED QUALIFICATIONS: <ul><li> 3+ years of experience in developing and maintaining production-grade codebases </li><li> Strong programming skills in Python and system-level languages (e.g. C/C++, Rust) </li><li> In-depth experience with version control systems like Git and collaborative development platforms like GitHub </li><li> Experience setting up and maintaining CI/CD principles through tools such as GitHub Actions and Jenkins </li><li> Strong understanding and experience in test-driven software development with knowledge of different testing methodologies such as unit testing, integration testing, and end-to-end testing </li><li> Excellent problem-solving, communication, and collaboration skills </li><li> Ability to work effectively in a fast-paced, multidisciplinary environment </li><li> Experience with containerization technologies like Docker and orchestration platforms like Kubernetes and Slurm </li><li> Experience with the challenges of scientific software development </li><li> Knowledge of software design patterns and architectures </li><li> Experience contributing to and/or maintaining open-source software projects or libraries </li><li> Familiarity with machine learning frameworks such as TensorFlow or PyTorch </li></ul> 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): <ul><li> Working knowledge of latest software and design standards. </li><li> Ability to define and solve logical problems for technical applications. </li><li> Knowledge of and ability to select, adapt, and effectively use a variety of programming methods. </li><li> Ability to recognize and recommend needed changes in user and/or operations procedures. </li><li> Basic knowledge of software engineering principles. </li><li> Strong knowledge of at least one programming language. </li></ul> CERTIFICATIONS & LICENSES: None PHYSICAL REQUIREMENTS : <ul><li> Constantly perform desk-based computer tasks. </li><li> Frequently sit, grasp lightly/fine manipulation. </li><li> Occasionally stand/walk, writing by hand. </li><li> Rarely use a telephone, lift/carry/push/pull objects that weigh up to 10 pounds </li></ul> - 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 work extended hours, evenings and weekends. The expected pay range for this position is $107,423 to $133,600 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 ( ) 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. <img src="https://www.jobg8.com/Tracking.aspx?K8u%2f7NQsWgo1Vl%2bL0S4Pn7qrNkk1KSrfs" width="0" height="0" />

Software Developer 1 (1 Year Fixed Term)

Stanford University, the Personalized Integrative Medicine Laboratory in the Radiology Department ( ) and the Urologic Cancer Innovation Laboratory ( ) is seeking a creative, highly motivated, Research and Development Scientist and Engineer 1 with an interest in developing platforms that integrate and deploy multimodal machine learning methods in clinical applications. The project is focused on developing a software platform to deploy our existing ultrasound-MRI models for prostate cancer detection in clinical practices. The position requires managing complex multi-modal data sets including clinical assessments, laboratory results, radiological images and pathological findings, to develop a user-friendly software that will encompass existing approaches and allows for easy integration of new models. The successful candidate will join the Department of Radiology at Stanford University and will work with a multi-disciplinary team of clinicians, statisticians, computer scientists, and trainees. This position is available immediately and has a 1-year duration, with possibility of extension based on funding availability and mutual agreement. Duties include : <ul><li> Design and develop specialized software and tools; coordinate detailed phases of work related to responsibility for part of a major project. </li><li> Develop technical and methodological solutions to complex engineering/scientific problems requiring independent analytical thinking and advanced knowledge. </li><li> Develop creative new or improved equipment, materials, technologies, processes, methods, or software important to the advancement of the field. </li><li> Contribute technical expertise, and perform basic research and development in support of programs/projects; act as advisor/consultant in area of specialty. </li><li> Optional: Contribute to portions of published articles or presentations; prepare and write reports; draft and prepare scientific papers. </li><li> Provide technical directions to other research staff, engineering associates, technicians, and/or students, as needed. </li></ul> - Other duties may also be assigned. DESIRED QUALIFICATIONS: <ul><li> Candidates should have prior experience in software and platform development and C++/python/docker/UIX programming, and be familiar with toolkits, e.g., ITK, opencv, sklearn. </li><li> Candidate should have prior experience with Designing User Interfaces, including image visualization and connect platforms with docker containers. </li><li> Candidates with experience in radiomics, segmentation, image registration are strongly encouraged to apply. </li><li> Candidates should have demonstrated ability to work independently, attention to details, be dedicated and self-motivated. </li><li> Collaborative team spirit, strong communication skills, positive attitude and adherence to highest ethical principles are necessary to be considered. </li><li> The candidate should have knowledge and experience in machine learning and deep learning, visualization, platform implementation. </li><li> The preferred candidate would also have experience with medical image processing, and traditional signal processing techniques. </li></ul> EDUCATION & EXPERIENCE (REQUIRED): Bachelor's degree and three years of relevant experience, or combination of education and relevant experience. Preferred candidates will have an M.S. with relevant experience or Ph.D. in Biomedical Engineering, Electrical Engineering, Biomedical Informatics, Computer Science or related fields. KNOWLEDGE, SKILLS AND ABILITIES (REQUIRED): <ul><li> Thorough knowledge of the principles of engineering and related natural sciences. </li><li> Demonstrated project management experience. </li></ul> PHYSICAL REQUIREMENTS : <ul><li> Frequently grasp lightly/fine manipulation, perform desk-based computer tasks, lift/carry/push/pull objects that weigh up to 10 pounds. </li><li> Occasionally stand/walk, sit, twist/bend/stoop/squat, grasp forcefully. </li><li> 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. </li></ul> - 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: <ul><li> May be exposed to high voltage electricity, radiation or electromagnetic fields, lasers, noise > 80dB TWA, Allergens/Biohazards/Chemicals /Asbestos, confined spaces, working at heights of 10 feet, temperature extremes, heavy metals, unusual work hours or routine overtime and/or inclement weather. </li><li> May require travel. </li></ul> WORK STANDARDS: <ul><li> Interpersonal Skills: Demonstrates the ability to work well with Stanford colleagues and clients and with external organizations. </li><li> Promote Culture of Safety: Demonstrates commitment to personal responsibility and value for safety; communicates safety concerns; uses and promotes safe behaviors based on training and lessons learned. </li><li> Subject to and expected to comply with all applicable University policies and procedures, including but not limited to the personnel policies and other policies found in the University's Administrative Guide, . </li></ul> The expected pay range for this position is $127,211 to $154,222 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 ( ) 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 a 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. The 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. <img src="https://www.jobg8.com/Tracking.aspx?1%2fwdEqK%2fok1FOvth%2bDDf9bKIlNxjAjKga" width="0" height="0" />

Research and Development Scientist and Engineer (1 Year Fixed-Term)

The 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 talented individuals specializing in mechanistic interpretability to develop and deploy scalable pipelines for analyzing and interpreting these models, helping us understand how the brain represents and processes information. The role combines rigorous engineering practices with cutting-edge research in model interpretability, working at the intersection of neuroscience and artificial intelligence.Role & Responsibilities: • Design and implement scalable pipelines for mechanistic interpretability analyses of large neural networks • Develop and automate feature visualization techniques to understand neural representations • Build tools for circuit discovery and geometric analysis of population activity • Create efficient, reproducible analysis workflows that can handle large-scale neural data • Collaborate with neuroscientists and ML researchers to design and implement novel interpretability methods • Maintain and optimize distributed computing infrastructure for running interpretability analyses • Document and share findings through technical reports and visualization tools • - Other duties may also be assignedWhat 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: In addition to applying to the position, please send your CV and one-page interest statement to: 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 Strong understanding of mechanistic interpretability techniques and research literature Expertise in implementing and scaling ML analysis pipelines Proficiency in Python and deep learning frameworks (i.e. PyTorch) Experience with distributed computing and high-performance computing clusters Strong software engineering practices including version control, testing, and documentation Familiarity with visualization tools and techniques for high-dimensional dataPreferred qualifications: Experience with feature visualization techniques (e.g., activation maximization, attribution methods) Knowledge of geometric methods for analyzing neural population activity Familiarity with circuit discovery techniques in neural networks Experience with large-scale data processing frameworks Background in neuroscience or computational neuroscience Contributions to open-source ML or interpretability tools Experience with ML experiment tracking platforms (W&B, MLflow)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 ( ) 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. <img src="https://www.jobg8.com/Tracking.aspx?Fo4bepkShYO7Es7w2%2bay4myJw%2bEXHCimc" width="0" height="0" />

Modeling/Interpretability Research Scientist (1 Year Fixed Term)

Bosch Group

Company Description "Invented for Life" drives us at Bosch and our vision of future mobility. Autonomous vehicles will change the way we move and at Bosch we are working on making this future a reality. We are now growing our team to solve some of the hardest automated driving problems, and are looking for experts for product engineering of AI-based Autonomous Driving systems. Job Description As the Senior Principal Engineer, E2E AI Training Framework for Autonomous Driving Systems, you will spearhead the development and optimization of the machinery that efficiently trains, optimizes, tests, and releases various E2E AI-based products (e.g. parking, driving, interior sensing) for different trim levels (entry, mid and high) within our L2+ ADAS stack. You will be responsible for defining and driving the technological roadmap for the AI machinery, ensuring its scalability, reliability, and performance. The ideal candidate must have prior industry experience in releasing AI-based L2+ systems, with a proven track record of translating innovative research into production-grade solutions. Key Responsibilities <ul><li>Define and drive execution of the technical roadmap and strategy for the E2E AI machinery, including training pipelines, optimization techniques, simulation and MLOps tooling.</li><li>Oversee the design, development, and testing of the E2E AI machinery and its interaction with data sources, model repositories, and development targets.</li><li>Collaborate closely with other functional tech leads (e.g. data engineering, infrastructure) to define and drive the overall architecture of the AI machinery ecosystem.</li><li>Guide the set-up of a development framework that enables fast evaluation and integration of emerging E2E AI solutions.</li><li>Guide the transition from research prototypes to production-ready solutions, ensuring performance optimization on automotive-grade hardware and scalability.</li><li>Leverage your prior industry experience in launching AI-based L2+ systems to implement best practices in system validation, testing (SIL/HIL), and continuous improvement.</li><li>Mentor and lead a high-caliber team of AI scientists and engineers, fostering a culture of innovation, collaboration, and technical excellence.</li></ul> Qualifications Basic Qualifications: <ul><li>Master's degree or Ph.D in Computer Science, Robotics, Electrical Engineering, AI, or a closely related field with a focus on autonomous systems</li><li>10+ years of experience in software development and system engineering for autonomous driving or ADAS applications</li><li>Proven industry experience in releasing AI-based L2+ systems, with a strong track record of successful product deployments</li><li>Deep knowledge of E2E AI stack solutions and training algorithms, including reinforcement learning, and imitation learning, as well as motion control and optimization techniques</li><li>Deep knowledge of AI frameworks such as TensorFlow and PyTorch</li><li>Deep knowledge in model optimization and embedded deployment of E2E AI stacks to embedded automotive hardware</li><li>Deep knowledge of cloud-based scalable training pipelines, MLOps, and CICD for training AI models with large-scale fleet datasets</li><li>Proven track record of leading the end-to-end development and successful deployment of complex AI-powered systems into production environments at scale</li></ul> Preferred Qualifications: <ul><li>Experience with simulation tools and testing methodologies (SIL/HIL) for autonomous systems.</li><li>Proficiency in programming languages such as Python and C++.</li><li>Strong understanding of automotive safety standards (ISO 26262, ASIL) and regulatory requirements for ADAS.</li><li>Exceptional leadership and communication skills, with the ability to inspire and manage cross-functional teams.</li><li>Strategic thinker with strong problem-solving abilities and a passion for innovation in autonomous driving technology.</li></ul> Additional Information The U.S. base salary range for this full-time position is $240,000 - $320,000. Within the range, individual pay is determined based on several factors, including, but not limited to, work experience and job knowledge, complexity of the role, job location, etc. This range does not include annual bonus percentage nor any other monetary considerations for the total compensation package. Your Recruiter can share more details about the specific salary range for this position during the interview process. In addition to your base salary, Bosch offers a comprehensive benefits package that includes health, dental, and vision plans; health savings accounts (HSA); flexible spending accounts; 401(K) retirement plan with an attractive employer match; wellness programs; life insurance; long term disability insurance; paid time off; parental leave. Pay ranges included in the postings, when included, generally reflect base salary; certain positions may include bonus, or additional benefits. Equal Opportunity Employer, including disability / veterans Bosch adheres to Federal, State, and Local laws regarding drug-testing. Employment is contingent upon the successful completion of a drug screen and background check. Candidates who have been offered the position must pass both screenings before their start date. <img src="https://www.jobg8.com/Tracking.aspx?00kgJ%2bE2%2bypDSv3RODr845gL0ZYlFuuId" width="0" height="0" />

Senior Principal Engineer- End-to-End AI Training Framework

Stanford University is seeking a Big Data Architect 1 for a 1 year fixed term (possibility of renewal) to design and develop applications, test and build automation tools and support the development of Big Data architecture and analytical solutions.About Us: The Department of Biomedical Data Science merges the disciplines of biomedical informatics, biostatistics, computer science and advances in AI. The intersection of these disciplines is applied to precision health, leveraging data across the entire medical spectrum, including molecular, tissue, medical imaging, EHR, biosensory and population data.About the Position: We are seeking an experienced ML Data Engineer to drive the programmatic curation, cleaning, and generation of healthcare data. In this role, you will focus exclusively on developing and maintaining automated, ML-accelerated pipelines that ensure high-quality data ready for machine learning applications. Your work will be pivotal in shaping the integrity of our data and supporting downstream predictive models in a complex healthcare environment. You Will Find This Position a Good Fit If: You are passionate about transforming raw healthcare data into valuable insights. You believe in the critical role of robust data curation in advancing machine learning in healthcare. You thrive in environments where you can work independently on complex data challenges while collaborating with multidisciplinary teams. You are excited to work with patient-level data and embrace challenges related to data diversity and complexity. Duties include: Design Big Data systems that are scalable, optimized and fault-tolerant. Work closely with scientific staff, IT professional and project managers to understand their data requirements for existing and future projects involving Big Data. Develop, test, implement, and maintain database management applications. Optimize and tune the system, perform software review and maintenance to ensure that data design elements are reusable, repeatable and robust. Contribute to the development of guidelines, standards, and processes to ensure data quality, integrity and security of systems and data appropriate to risk. Participate in and/or contribute to setting strategy and standards through data architecture and implementation, leveraging Big Data, analytics tools and technologies. Work with IT and data owners to understand the types of data collected in various databases and data warehouses. Research and suggest new toolsets/methods to improve data ingestion, storage, and data access. Key Responsibilities: Data Pipeline Engineering: Design, implement, and maintain robust pipelines for the programmatic cleaning, transformation, and curation of healthcare data. Develop automated processes to curate and validate data, ensuring accuracy and compliance with healthcare standards (e.g. OMOP CDM, FHIR). ML Data Engineering: Leverage core machine learning techniques to generate datasets, clean existing health records, join heterogeneous data sources, and enhance data quality for model training. Implement innovative solutions to detect and correct data inconsistencies and anomalies in large-scale healthcare datasets. Healthcare Data Expertise: Work extensively with patient-level health data, ensuring that data handling practices adhere to industry regulations and ethical standards. Utilize the OMOP Common Data Model (OMOP CDM) to standardize and harmonize disparate healthcare data sources, enhancing interoperability and scalability. Collaboration & Continuous Improvement: Collaborate closely with data scientists, clinical informaticians, and engineers to align data engineering practices with analytical and clinical requirements. Continuously monitor, troubleshoot, and optimize data workflows to support dynamic research and operational needs.The expected pay range for this position is $157,945 to $177,385 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 () 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 a reasonable accommodation for any part of the application or hiring process should contact Stanford University Human Resources at . For all other inquiries, please submit 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. Stanford welcomes applications from all who would bring additional dimensions to the University's research mission. DESIRED QUALIFICATIONS: 3+ years of experience in software development and data engineering with a strong focus on data cleaning, transformation, and creation. Proficiency in Python and experience with data processing libraries (e.g., Pandas, Polars, NumPy). Hands-on experience in building and maintaining automated data pipelines for large-scale data processing. Familiarity with machine learning frameworks (e.g., PyTorch, JAX, scikit-learn) as applied to data quality and augmentation tasks. Expertise in working with healthcare data, including familiarity with the OMOP Common Data Model (OMOP CDM). Strong experience in a Linux environment and comfort with UNIX command-line tools. Proven ability to work collaboratively in multidisciplinary teams and communicate technical concepts effectively. PREFERRED QUALIFICATIONS: Experience with cloud platforms (e.g., GCP, AWS, or Azure) and distributed computing frameworks. Proficiency with version control systems (e.g., Git) and containerization tools (e.g., Docker). Familiarity with healthcare data standards and regulatory requirements. EDUCATION & EXPERIENCE (REQUIRED):Bachelor's degree in scientific or analytic field and five years of relevant experience, or a combination of education and relevant experience.KNOWLEDGE, SKILLS AND ABILITIES (REQUIRED): • Knowledge of key data structures algorithms, and techniques pertinent to systems that support high volume, velocity, or variety datasets (including data mining, machine learning, NLP, data retrieval). • Experience with relational, NoSQL, or NewSQL database systems and data modeling, structured and unstructured. • Experience in parallel and distributed data processing techniques and platforms (MPI, Map/Reduce, Batch). • Experience in scripting languages and experience in debugging them, experience with high performance/systems languages and techniques. • Knowledge of benchmark software development and programmable fields/systems, ability to analyze systems and data pipelines and propose solutions that leverage emerging technologies. • Ability to use and integrate security controls for web applications, mobile platforms, and backend systems. • Experience deploying reliable data systems and data quality management. • Ability to research, evaluate, architect, and deploy new tools, frameworks, and patterns to build scalable Big Data platforms. • Ability to document use cases, solutions and recommendations. • Demonstrated excellence in written and verbal communication skills.CERTIFICATIONS & LICENSES:NonePHYSICAL REQUIREMENTS :• Frequently sit, grasp lightly, use fine manipulation and perform desk-based computer tasks, lift, carry, push pull objects that weigh to ten pounds. • Occasionally sit, use a telephone or write by hand. • Rarely kneel, crawl, climb, twist, bend, stoop, squat, reach or work above shoulders, sort, file paperwork or parts, operate foot and hand controls. - 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.<img src="https://www.jobg8.com/Tracking.aspx?qn2dWMJXE5OUYhjpmgXExjIqwGbtR5Eaq" width="0" height="0" />

ML Data Engineer - Healthcare Data Curation & Cleaning (1 Year Fixed Term)

Explore 50+ Machine learning engineer in California this October. Find roles across top companies and apply now to boost your career.