Machine Learning Engineer specializing in building robust production ML systems, with expertise in computer vision, audio processing, and generative diffusion models. I focus on optimizing inference for speed and efficiency, maximizing hardware potential, and ensuring seamless scalability.
ML Engineer @ Dreamflux
- Building AI-driven characters that evolve through layered memory structures
- Creating multi-agent environments where narratives unfold organically with spatial intelligence and adaptive roles
- Researching long-term contextual retention in AI systems
ML Engineer @ Playjump
- Orchestrated serverless diffusion workflows for consistent character rendering
- Built rapid video enhancement pipelines using diffusion models
- Optimized inference systems for production deployment
Resident @ Lossfunk
- Focused on model compression and efficient deployment
- ComfyUI Extensions: Developing advanced temporal upscalers for fluid video restoration
- Diffusion APIs: Engineering lightweight APIs that harness diffusion models for narrative visuals
- Memory Systems: Deep diving into research papers on long-term contextual retention in AI systems
- 3D Avatar Generation: Bridging 2D diffusion models with volumetric representations
- Shader Generation: Tackling text-to-shader and image-to-shader pipelines that transform natural language and visuals into programmable graphics code
- Diffusion Models: Production deployment, optimization, and custom pipeline development
- ML Systems: Scalable inference systems, model optimization, and hardware acceleration
- Multi-Agent Systems: Building complex agentic workflows and orchestration
- Computer Vision: Image/video processing, temporal consistency, and upscaling
- Infrastructure as Code: Automated deployment and infrastructure management
