Machine Learning Engineer Intern

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

What We're Looking For
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

We're looking for someone who:

• 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

We welcome candidates from a variety of backgrounds:

• 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.