Modeling / Interpretability Research Scientist (1 Year FixedTerm)

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

visualization techniques to understand neural

representations

geometric analysis of population activity

efficient, reproducible analysis workflows that can handle

large-scale neural data

and ML researchers to design and implement novel interpretability

methods

infrastructure for running interpretability analyses

Document and share findings through technical reports and

visualization tools

assigned

What we

offer :

fundamental research questions in AI and neuroscience

vibrant team of engineers and scientists in a project dedicated to

one mission, rooted in academia but inspired by science in

industry.

and biological neural networks

computing infrastructure

package

multiple disciplines

with access to its world-class research community

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

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

data

Preferred

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) :

knowledge of the principles of engineering and related natural

sciences.

experience.

CERTIFICATIONS

LICENSES : None

PHYSICAL

REQUIREMENTS

lightly / fine manipulation, perform desk-based computer tasks,

lift / carry / push / pull objects that weigh up to 10 pounds.

grasp forcefully.

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.

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 :

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.

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.