.png){kind=logo}
Dylan Tang
Intern Software Developer and ML Researcher specializing in medical imaging and computer vision
Connect with Dylan
Dylan already has a relationship with Reval, so a warm intro from us gets a much better response than cold outreach.
Recommended
Already have an account?
About
AI/ML practitioner with experience spanning audio/LLM applications (built "Iota" using Whisper, tiktoken, and a local Ollama-served LLM) and healthcare ML (Facemed.ai; UChicago Radiology). Demonstrates a production-oriented mindset—focus on data/model fit, deterministic field testing, and operational safeguards—and has improved research evaluation workflows via a hash-table-based concurrent model tracking approach.
Experience
Education
Key Strengths
- Built an audio-to-LLM application pipeline (Whisper transcription + tokenization + downstream LLM response)
- Hands-on experience adapting AI systems to real-world hardware/audio constraints (multi-channel mic configuration, 16 kHz processing)
- Strong understanding of why static training data/context windows limit real-world/embodied deployments (latency, resource constraints, dynamic environments)
- Applied ML to healthcare context; identified transferability issues from clean/preprocessed data to real patient tests (Facemed.ai)
- Improved research ML evaluation scalability by designing a hash-table-based tracking system enabling concurrent multi-model evaluation
- Production-minded ML approach: data/model fit, deterministic reliability, monitoring/logging, and rollback controls
Discover more candidates like Dylan
Search across thousands of pre-screened, high-quality, high-intent candidates on Reval.
Search Talent