Machine Learning Intern

# Machine Learning Intern: Computer Vision & AI Film Evaluation (Human-in-the-Loop)
Company: RcruitLync
Location: Remote (US) / Flexible
Employment Type: Internship (Full-Time or Part-Time)
Website: https://rcruitlync.com/
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### About RcruitLync
RcruitLync is modernizing athletic recruiting and academic discovery for student-athletes nationwide. We combine real-time communication tools, verified scouting profiles, academic compliance tracking, and automated video intelligence into a unified platform.
We are training our multimodal sports computer vision models to dissect, grade, and analyze game film with the tactical precision of a seasoned collegiate scout. To get there, we need a sharp, detail-oriented Machine Learning Intern to serve as the critical human-in-the-loop bridge between raw athlete film and production-grade AI analysis.
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### The Role
Machine learning models are only as good as the ground-truth feedback that guides them. In this role, you will work side by side with senior computer vision and video analysis engineers to evaluate, score, and benchmark our AI video analysis pipeline across thousands of hours of athletic film.
You will audit model outputs for action detection, player tracking, mechanics assessment, and tactical play breakdown. Your evaluations will directly shape our active learning loops, fine-tuning datasets, and RLHF (reinforcement learning from human feedback) pipelines.
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### What You Will Do
- Grade and benchmark AI-generated film analyses: Audit model outputs for accuracy across play segmentation, player tracking, event tagging, and athletic movement grading.
- Establish ground truth: Annotate keyframes, identify kinematic errors or tracking drift, and build gold-standard validation sets for model evaluation.
- Identify edge cases and failure modes: Root out false positives in noisy, varied gym and field footage (lighting variations, camera angles, occlusion, fast transitions).
- Partner with engineering: Collaborate with our backend video pipeline and ML teams to translate domain observations into quantifiable error metrics, prompt improvements, and model training tasks.
- Shape the AI scout: Help define qualitative and quantitative scoring criteria so our automated breakdown reflects what college coaches and scouts actually evaluate on film.
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### What We Are Looking For
- Academic Background: Currently pursuing or recently completed a degree in Computer Science, Data Science, Machine Learning, Sports Analytics, or a related quantitative discipline.
- Deep Sports IQ: Strong understanding of high school and collegiate sports (basketball, football, track, or soccer). You know spacing, defensive schemes, mechanics, and what makes a legitimate highlight.
- Technical Literacy: Basic familiarity with Python, computer vision concepts (object detection, pose estimation, temporal action localization), or ML data annotation workflows.
- Relentless Attention to Detail: You notice dropped frames, misidentified jersey numbers, and subtle body positioning flaws that standard algorithms miss.
- Analytical Mindset: Ability to categorize failure patterns systematically rather than treating errors as isolated glitches.
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### Bonus Points
- Experience with video tools (OpenCV, FFmpeg) or ML labeling frameworks (Label Studio, CVAT, Roboflow).
- Prior experience as a competitive student-athlete, team video coordinator, or student manager.
- Familiarity with multimodal LLM evaluation (e.g., Gemini Vision, GPT-4o) and prompt engineering.
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### Why Join RcruitLync?
- Real Production Impact: Your evaluations go directly into training models that serve thousands of high school athletes aiming for college opportunities.
- Mentorship: Work directly with senior video analysis engineers and product leadership in an agile, high-growth environment.
- Portfolio Experience: Gain hands-on experience in RLHF, computer vision evaluation pipelines, and active learning architecture.
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### How to Apply
Send your resume, LinkedIn profile, and a brief note about your favorite sport and what you look for when analyzing game tape to careers@rcruitlync.com with the subject line: "ML Intern - AI Film Analysis - [Your Name]".
Explore the platform at https://rcruitlync.com/

Work arrangement
Yes