Kubelt
Fellow in Research Engineering, Kempner Institute
Kubelt, Oklahoma City, Oklahoma, United States
The Protocol Labs Network is an ecosystem of teams pushing the boundaries of decentralized technologies, research, and open-source innovation. Explore opportunities across the network and join the mission.
Fellow in Research Engineering, Kempner Institute Title: Fellow in Research Engineering, Kempner Institute
School: Faculty of Arts and Sciences
Department/Area: Kempner Institute for the Study of Natural and Artificial Intelligence
Position Description The Engineering Fellowship Program at
Kempner Institute at Harvard University
offers a structured opportunity for recent graduates (fellows) to further their experience in AI/ML engineering. The program offers fellows a comprehensive, hands‑on learning experience that prepares them for a successful career in the AI/ML field.
Engineering Fellows will interact directly with a member of the Kempner Institute Research Engineering team to advance their skills and understanding of advanced technologies. This includes developing cutting‑edge AI/ML models and datasets; learning how to take advantage of unparalleled computing resources in the academic environment by optimizing AI/ML models including scaling models across a large set of GPUs; building or optimizing LLMs to tackle new, complex tasks; developing new models of brain circuits and function; and learning software engineering best practices including how to develop and disseminate reliable, reproducible open-source AI/ML scientific software packages.
Products resulting from the fellows activities such as code, models, or datasets, may be published on Kempner Institute public channels, including
GitHub ,
Hugging Face , or our
Research Blog .
The fellowship program is a full-time (35-hour per week) position. Fellows are appointed for a minimum 6 month commitment, which is typically renewed for an additional 6 month term based on satisfactory performance and mutual interest. The program is fully on‑site, in person in the Kempner Institute, 6th floor, Science and Engineering Complex in Allston, MA. Remote work is not possible in this position. Applicants must be legally eligible to work in the United States. We are not able to provide visa sponsorship for this position.
Basic Qualifications
Proficiency in coding (Python) and deep learning frameworks (PyTorch) with a drive to enhance these skills.
Familiarity with one of the AI/ML fields like Natural Language Processing, Computer Vision, Reinforcement Learning, generative models, or a strong interest in exploring them.
Basic data preprocessing, feature engineering, and model evaluation, or a strong willingness to gain hands‑on experience.
Eagerness to learn HPC concepts, including parallel computing, distributed systems, and optimization.
Analytical skills, problem‑solving abilities, and a growth mindset.
Additional Qualifications Applicants should be within
three years of graduation
from a bachelor’s or master’s degree at the time of application.
Special Instructions Applicants should submit a
resume
and a
cover letter
which:
Briefly describes your educational background (50 words).
Describes a project or experience where you used Python for coding or developing AI/ML models (100 words max).
Describes any hands‑on experience you have in data preprocessing, feature engineering, and model evaluation (100 words max).
Lists any additional skills or technologies you are proficient in (e.g., C++, Julia, AWS, TensorFlow, etc.) (50 words or less).
Cover Letters: Ratings Cover letters should also include a rating for your:
A. Proficiency in Python
B. Experience with Deep Learning Frameworks (e.g., PyTorch)
C. Familiarity with HPC including running serial or distributed jobs
D. Familiarity with AI/ML fields
Using the following ratings:
(2) Intermediate – have used it in projects
(3) Advanced – extensive experience and deep understanding in multiple successful projects
EEO/Non-Discrimination Commitment Statement Harvard University is committed to equal opportunity and non‑discrimination. We seek talent from all parts of society and the world, and we strive to ensure everyone at Harvard thrives. Our differences help our community advance Harvard’s academic purposes. Harvard has an equal employment opportunity policy that outlines our commitment to prohibiting discrimination on the basis of race, ethnicity, color, national origin, sex, sexual orientation, gender identity, veteran status, religion, disability, or any other characteristic protected by law or identified in the university’s non‑discrimination policy. Harvard’s equal employment opportunity policy and non‑discrimination policy help all community members participate fully in work and campus life free from harassment and discrimination.
Supplemental Questions Required fields are indicated with an asterisk (*).
#J-18808-Ljbffr
Fellow in Research Engineering, Kempner Institute Title: Fellow in Research Engineering, Kempner Institute
School: Faculty of Arts and Sciences
Department/Area: Kempner Institute for the Study of Natural and Artificial Intelligence
Position Description The Engineering Fellowship Program at
Kempner Institute at Harvard University
offers a structured opportunity for recent graduates (fellows) to further their experience in AI/ML engineering. The program offers fellows a comprehensive, hands‑on learning experience that prepares them for a successful career in the AI/ML field.
Engineering Fellows will interact directly with a member of the Kempner Institute Research Engineering team to advance their skills and understanding of advanced technologies. This includes developing cutting‑edge AI/ML models and datasets; learning how to take advantage of unparalleled computing resources in the academic environment by optimizing AI/ML models including scaling models across a large set of GPUs; building or optimizing LLMs to tackle new, complex tasks; developing new models of brain circuits and function; and learning software engineering best practices including how to develop and disseminate reliable, reproducible open-source AI/ML scientific software packages.
Products resulting from the fellows activities such as code, models, or datasets, may be published on Kempner Institute public channels, including
GitHub ,
Hugging Face , or our
Research Blog .
The fellowship program is a full-time (35-hour per week) position. Fellows are appointed for a minimum 6 month commitment, which is typically renewed for an additional 6 month term based on satisfactory performance and mutual interest. The program is fully on‑site, in person in the Kempner Institute, 6th floor, Science and Engineering Complex in Allston, MA. Remote work is not possible in this position. Applicants must be legally eligible to work in the United States. We are not able to provide visa sponsorship for this position.
Basic Qualifications
Proficiency in coding (Python) and deep learning frameworks (PyTorch) with a drive to enhance these skills.
Familiarity with one of the AI/ML fields like Natural Language Processing, Computer Vision, Reinforcement Learning, generative models, or a strong interest in exploring them.
Basic data preprocessing, feature engineering, and model evaluation, or a strong willingness to gain hands‑on experience.
Eagerness to learn HPC concepts, including parallel computing, distributed systems, and optimization.
Analytical skills, problem‑solving abilities, and a growth mindset.
Additional Qualifications Applicants should be within
three years of graduation
from a bachelor’s or master’s degree at the time of application.
Special Instructions Applicants should submit a
resume
and a
cover letter
which:
Briefly describes your educational background (50 words).
Describes a project or experience where you used Python for coding or developing AI/ML models (100 words max).
Describes any hands‑on experience you have in data preprocessing, feature engineering, and model evaluation (100 words max).
Lists any additional skills or technologies you are proficient in (e.g., C++, Julia, AWS, TensorFlow, etc.) (50 words or less).
Cover Letters: Ratings Cover letters should also include a rating for your:
A. Proficiency in Python
B. Experience with Deep Learning Frameworks (e.g., PyTorch)
C. Familiarity with HPC including running serial or distributed jobs
D. Familiarity with AI/ML fields
Using the following ratings:
(2) Intermediate – have used it in projects
(3) Advanced – extensive experience and deep understanding in multiple successful projects
EEO/Non-Discrimination Commitment Statement Harvard University is committed to equal opportunity and non‑discrimination. We seek talent from all parts of society and the world, and we strive to ensure everyone at Harvard thrives. Our differences help our community advance Harvard’s academic purposes. Harvard has an equal employment opportunity policy that outlines our commitment to prohibiting discrimination on the basis of race, ethnicity, color, national origin, sex, sexual orientation, gender identity, veteran status, religion, disability, or any other characteristic protected by law or identified in the university’s non‑discrimination policy. Harvard’s equal employment opportunity policy and non‑discrimination policy help all community members participate fully in work and campus life free from harassment and discrimination.
Supplemental Questions Required fields are indicated with an asterisk (*).
#J-18808-Ljbffr