CalCritters
Interactive campus ARG where students scan QR codes to meet LLM-driven characters. Reached 150+ active users.
Aspiring Machine Learning Engineer
BETODAMIAN
Building and scaling large models and ML systems. Currently developing genomic foundation models at Lawrence Berkeley National Lab.
// autoregressive sample · genomeocean
About
UC Berkeley Data Science
I work on ML systems and large-model scaling: inference optimization, distributed training, and transformer architectures.
Right now I'm at the Joint Genome Institute working on GenomeOcean, building generation and evaluation pipelines from scratch.
I focus on high-performance inference and training: FlashAttention kernels, quantization, and multi-GPU scaling on HPC clusters.
I'm graduating in December 2026 and open to ML engineering roles. Outside of work I make video games and produce music.
Go To Beto's Creative Portfolio
Experience
Where I've been working
ML Research Intern
Lawrence Berkeley National Laboratory · Joint Genome Institute · Berkeley, CA
May 2026 - Present
- Developing and evaluating GenomeOcean, a large genomic foundation model, including generation and evaluation pipelines.
- Built generation and evaluation pipelines using LLM sampling strategies and naturalness scoring across 1M+ sequences, improving F1 by 250%.
- Optimized inference with FlashAttention-2 and 4-bit quantization (+125% throughput); scaled training across 20 GPUs on the Lawrencium HPC cluster.
Programming Instructor
The Coder School · California
Jul 2022 - Present
- Teaching programming and software design to 30+ students across 3 locations, building 60 reusable Python and JavaScript project codebases.
- Developing curriculum modules on foundational coding principles and modern software architecture for beginner learners.
- Providing technical mentorship and debugging support, fostering a collaborative environment for technical growth.
Portfolio
Highlighted Projects
Engineering scalable ML systems and foundation models at the intersection of computer vision and large language models.
AI-Powered Tutoring Note Assistant
Chrome extension that turns tutor notes into structured session summaries via the Gemini API. Saved ~10 min/session for 20+ tutors.
Real-Time ONNX Hand Tracking
Real-time computer-vision system tracking 21 hand landmarks at 120 FPS, no MediaPipe dependency.
Zonez
Web app that aggregates student availability across time zones to visualize overlapping study windows. Helped 50+ students coordinate.
Toolkit
Key skills
Languages
- Python
- C++
- C
- Java
- SQL
- JavaScript
ML & Modeling
- PyTorch
- Hugging Face Transformers
- ONNX Runtime
- NumPy · Pandas
- Transformer Architectures
- Quantization (GPTQ/AWQ/GGUF)
DevOps
- AWS · Azure
- HPC Clusters (SLURM)
- CUDA · Linux/SSH
- Git · REST APIs
- Node.js · React