Machine Learning Engineer
Hi, I'm Jacob.
I'm a machine learning engineer working on machine-learning systems and RL — training and serving large models, GPU kernels, and the infrastructure around them. I like understanding systems from first principles and writing the explanation I wish I'd had.
Explore
ML Fundamentals
A first-principles reference library: ML & deep-learning foundations, generative models, reinforcement learning, GPU kernels & LLM serving (CUDA / Triton / vLLM / SGLang), distributed training, agentic systems, data-intensive systems, and systems design.
Browse the library →Data-Intensive Systems
A DDIA-inspired first-principles track: data models, storage engines, schema evolution, replication, partitioning, transactions, consistency, consensus, batch, streams, CDC, and derived-data correctness.
Start the data systems track →Agentic AI Systems
A linear architecture track for building reliable agents: contracts, control flow, tools, MCP, RAG, memory, multi-agent protocols, guardrails, evaluation, monitoring, and cost.
Start the agentic track →Reinforcement Learning
One linear track: MDPs, value & policy methods, TRPO/PPO, RLHF/GRPO, post-training systems, and twenty applied domains — first principles throughout.
Start the RL track →Writing
An archive of earlier posts on algorithms, systems, and engineering — design patterns, distributed systems, compilers, and databases.
Read the archive →