As time permits, and not in conflict with any full-time employ I might hold, I am available for consulting and advisory work in the following areas:

Machine learning

My professional background is primarily in machine learning. Most recently, I spent 4+ years at ASAPP where I built NLP technologies for customer service automation and augmentation. Specifically, I built production systems for intent classification, personalized text recommendation and conversation summarization. In addition, I researched and developed methods for dialog generation, dialog segmentation, "procedure induction" in goal-oriented dialog and online learning—supervised by Dr. Kilian Q. Weinberger. Examples of my work can be found e.g. here and here. Throughout this time, I worked with an (extremely) wide range of NLP tools and techniques, including the two you likely care most about in 2023, PyTorch and LLMs 😊 Lately, I've been thinking a lot about our future with the latter.

In addition, I've maintained a keen interest in "statistical" machine learning throughout the years, writing on topics like approximate inference, Bayesian methods, generative models, PPLs, and many more. I even applied for PhD programs in this space in 2021, wherein I hoped to bring techniques from NLP to simulation-based inference.

Taken together, I'd be a good person to hire for:

  • Applied research: researching and prototyping novel ML-based products and solutions.
  • Software engineering: building production ML systems.
  • Advisory: ML product development, infrastructure and tooling, data collection and labeling, team structure and hiring, etc.

Multi-agent systems

After ASAPP, I took time to explore topics in complex systems and simulation in the context of crypto. During that time, I spent a ~year working at Block Science where I built dynamical pricing models for a peer-to-peer compute network, as well as simulations of the rewards economy implicit in a "we pay you for your stock picks" hedge fund. In addition, I worked on a variety of personal projects in this space. Currently, I work on the Core Risk team at Gauntlet where I build algorithms and systems for statistical risk management in DeFi.

Taken together, I'd be a good person to hire for:

  • Applied research: researching and prototyping models of multi-agent systems.
  • Software engineering: building production simulation systems.
  • Advisory: simulation product development, infrastructure and tooling, team structure and hiring, etc.


I've been learning Rust since 2021. I've built a few small projects in the language, including a simple simulation framework for generalized dynamical systems. I'd love to do more.

Taken together, I'd be a good person to hire for:

  • Tooling: Rust-based tooling for ML and simulation. For instance, writing NLP tokenizers in Rust for use in Python, or a Rust-based simulation engine.
  • Software engineering: building production systems in Rust.

Domains of interest

Here are some domains I'd be particularly interested in working in:

  • Autonomous digital agents
  • Autonomous physical agents, e.g. autonomous vehicles
  • Education
  • Foreign language learning
  • Robotics
  • Logistics and transportation
  • Manufacturing
  • Defense

This said, I'm open to working in any domain where I can learn something new and interesting amongst fantastic peers.


For rates and availability, please email me at williamabrwolf [at] gmail [dot] com. Additional social links can be found below.

Cheers 😊

© Will Wolf 2020

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