Hi, I'm Alek Dimitriev - Inference at Anthropic
I thrive at the intersection of deep learning and large language models, focusing on the critical challenges of AI inference. My passion lies in bridging cutting-edge academic research with real-world applications to bring advanced AI systems to life efficiently and responsibly.
At a glance
Curated signals on strengths, focus areas, and how they can help.
Pioneered research in backpropagating through discrete variables during PhD at UT Austin.
Developed and optimized inference systems for Google's Gemini large language models.
Can share insights on optimizing AI inference for LLMs and novel backpropagation approaches.
🚀 Career trajectory
Doctoral Research
Completed a PhD at UT Austin, focusing on novel methods for deep neural networks, particularly backpropagation through discrete variables.
✦ Deep Learning Research
✦ Machine Learning Theory
✦ PhD
Machine Learning Engineer at Google
Applied ML expertise to large-scale projects, including Gemini's finetuning and inference systems.
✦ Large Language Models
✦ AI Inference
✦ Industry Engineering
Member of Technical Staff at Anthropic
Currently focusing on the critical area of AI inference, pushing the boundaries of model deployment and efficiency.
✦ AI Inference
✦ LLM Deployment
✦ Cutting-Edge AI
💪🏻 Superpowers
AI Inference Pioneer
Expertise in optimizing and deploying large-scale AI models.
✦ Specializing in the technical challenges of AI inference at Anthropic.
✦ Developed and fine-tuned inference systems for Google's Gemini models.
✦ Contributed foundational research in backpropagation for discrete variables.
Bridging Academia and Industry
Translating cutting-edge research into practical AI solutions.
✦ Leveraging PhD research in deep learning for real-world applications.
✦ Applying advanced machine learning techniques from academic rigor to industry demands.
✦ Experienced in both theoretical exploration and applied engineering.
Machine Learning Systems Architect
Designing and building efficient and scalable ML infrastructure.
✦ Deep understanding of deep learning and LLM architectures.
✦ Skilled in optimizing model performance for inference.
✦ Proficient in multiple programming languages and data analysis techniques.
I'm excited about
✦ Collaborating with leading AI researchers and engineers.
✦ Exploring new frontiers in AI inference and model optimization.
✦ Connecting with professionals passionate about responsible AI development.
I can help with
✦ Sharing insights on optimizing AI inference for LLMs.
✦ Providing technical guidance on deep learning model development.
✦ Discussing innovative approaches to discrete variable backpropagation.
I would love your help on
✦ Identifying emerging trends in AI hardware acceleration.
✦ Connecting with experts in novel neural network architectures.
✦ Discovering opportunities for cross-disciplinary AI research collaborations.