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Machine Learning Engineer InternYoung World Physical Education • Putnam, Alabama, United States
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Machine Learning Engineer Intern

Young World Physical Education
  • US
    Putnam, Alabama, United States
  • US
    Putnam, Alabama, United States
Postuler Maintenant

À propos

Machine Learning Engineer Intern Job ID:
5079518
Application Deadline:
Posted until filled
Posted:
Apr 03, 2025 12:00 AM (UTC)
Starting Date:
Jun 16, 2025
Job Description AI + Elite Basketball | Summer 2025 Duration: ~8 weeks (June 16 ~ Aug 11) Onsite (Putnam, CT), with housing & meals supported through PSA’s campus Type: Unpaid internship, with potential path into a deeper role beyond summer Open to candidates with CPT, OPT, and H-1B
About Us This internship is hosted by
PAI (Precision Athletics Intelligence) , a new AI athletic program by
Putnam Science Academy (PSA)
— one of the most elite basketball-focused high schools in the U.S.
PSA has won
5 National Prep School Basketball Championships
in 8 years, most recently in
March 2025
The school’s mission is to deliver
world‑class private high school education
while developing players for
NCAA and NBA levels
PAI is built to bring
AI into high‑performance sports and education , starting with this summer MVP project
This is PAI’s
first technical initiative , aiming to create a foundational performance analysis platform for PSA’s nationally ranked basketball program — with high visibility and real‑world application from day one.
What You’ll Build You’ll join a small, focused team building an end‑to‑end system to:
Automatically analyze practice footage
Detect key actions (shooting, movement, defensive effort)
Deliver structured feedback to coaches and players within minutes
This product is aiming China Market and it will serve elite athletes and coaching staff immediately, with long‑term potential to scale across teams and domains.
Your Role As an ML intern, you'll work on the core computer vision pipelines that power the system.
Responsibilities
Use or fine‑tune models like
YOLOv8 ,
OpenPose , or
MediaPipe
Build pipelines to extract training insights from video
Process raw frames into structured data (e.g. player tracking, shot detection)
Evaluate models on accuracy, reliability, and latency
Deliver usable outputs via APIs to frontend/dev teams
Write modular, reproducible code for experimentation and iteration
Core Skills
Strong Python skills; comfortable with Jupyter, scripting, and code structure
Experience with PyTorch or TensorFlow — or fast learning capability
Comfortable using OpenCV and working with image/video data
Familiar with Git and collaborative development environments
Fluent spoken Chinese (Mandarin)
Mindset
Has
real confidence
in their ability to learn fast and figure things out independently
Can take
vague or high‑level product goals , and turn them into working code
Works through ambiguity with speed, structure, and clarity
Cares about doing real work that gets used — not just academic experiments
Is genuinely
interested in basketball
and understands the game at a basic level
Thrives in a builder‑style environment with ownership, speed, and open problems
Bonus (Not Required)
Projects involving video analysis, pose estimation, or CV pipelines
Experience with DeepSORT, sports heatmaps, or action recognition
Familiarity with serving models via FastAPI, Flask, or REST endpoints
Background as a player, coach, or data analyst in sports
Who Can Apply
Undergraduates
(junior/senior preferred) with strong project experience
Master’s students
in CS, AI, or related fields
PhD students
focused on applied machine learning
Self‑taught engineers
— if you’ve built real things, we want to see them
We value your ability to build and think clearly over your academic label.
Why This Matters This is not a typical early‑stage internship.
While our tech team is just starting out, our platform isn’t. You’ll be building within a system that already has:
A
championship‑level basketball program
Immediate real‑world users: athletes and coaches with daily training needs
A founder with full access to decision‑making, facilities, and execution
A high‑trust environment where things move fast, and feedback is real
In many ways, PSA provides what most startups seek after Y Combinator:
A live environment, institutional support, immediate demand, and the room to build and scale
If you have:
Strong learning ability
Clear technical thinking
Ambition to turn huge ideas into real systems
…and you’re excited by sports, education, AI, and building things from scratch — you’ll thrive here.
Job Requirements
Bachelor degree preferred.
Contact Information
TIEQIANG DING, PRESIDENT
Putnam Science Academy Main Office
Phone: 860-928-5010
Email: TDING@PUTNAMSCIENCE.ORG
#J-18808-Ljbffr
  • Putnam, Alabama, United States

Compétences linguistiques

  • English
Avis aux utilisateurs

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