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 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:
In addition to applying to the position, please send your CV and one-page interest statement to: recruiting@enigmaproject.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 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
WORKING CONDITIONS:
• May be exposed to high voltage electricity, radiation or electromagnetic fields, lasers, noise, allergens/biohazards/chemicals/asbestos, confined spaces, working at heights, temperature extremes, heavy metals, unusual work hours or routine overtime and/or inclement weather.
• May require travel.
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.
