How I reduce the trial-and-error of machine learning development:

  • Facilitate knowledge sharing amongst stakeholders, domain experts, and engineers
  • Guide machine learning engineers to the most effective models and experiments
  • Handle the challenges of real world data
  • Follow industry best practices
  • Create a clear project roadmap
  • Design generalizable models
  • Properly validate models
  • Smoothly navigate through challenges
  • Help build an interdisciplinary team

Machine Learning Consulting Options

Custom Consulting

Starting at $30,000

Are you struggling to keep your machine learning projects on the path to success? Are you afraid your machine learning project will turn into an endless stream of failed experiments? What if you had a clear ML strategy for your team? I can keep you abreast of the latest research for your application, help you tackle unique data challenges, provide hiring advice, and more. With a custom engagement, we’ll define the scope to meet the needs of your team.

Schedule a call to learn more



Are you confident that your machine learning models are the best ones for your data? Do your models accommodate challenges like domain shifts, noisy labels, heterogeneous images, or small training sets? My Machine Learning Diagnostic provides recommendations to give your team a clear perspective on what your challenges really are and how you can better apply data- and model-centric techniques to create more robust and generalizable models.

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1 Hour Strategy Session


What if you could talk to an expert quickly? Are you facing a specific machine learning challenge? Do you have a pressing question? Schedule a 1 Hour Strategy Session now. Ask me anything about whatever challenges you’re facing. I’ll give you no-nonsense advice that you can put into action immediately.

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These services might not be a good fit if you’re only looking for:

  • How to setup your data infrastructure or annotate your data
  • Which MLOps tools to use
  • Model training and validation done for you
  • Model deployment

Schedule a free Machine Learning Discovery Call to discuss which service is best for you

Work With Me

Don’t Outsource…
Insource - and Empower Your Team

While machine learning certainly can bring new insights, precision, and efficiency, it takes time to build the technology to do it. And the path to a successful solution is generally not linear.

Many companies outsource machine learning projects. While this can be successful for well-defined applications with a limited scope, high impact projects are different. These projects are often part of a company’s core technology, so they prefer to keep the intellectual property development in house. But they may not have navigated the unique complexities of a machine learning project before. I can help you build the technology and your team in house, ensuring a smoother path to success.

My goal is not just to get you to an ideal solution but to ensure your team also understands how it works so that they can modify it and adapt to new challenges that arise. I will be there to help you navigate these obstacles as needed, but I consider my role most successful if I have transferred this knowledge to your team.

Build an Interdisciplinary Team

I’ve worked with teams spanning many different disciplines and the best results tend to come from a combination of

  • Pathologists, remote sensing scientists, or other domain experts who understand the data and how it is collected,
  • Data engineers who gather and organize it,
  • Machine learning engineers who train and analyze models, and
  • Software engineers who bring all the pieces together and create a robust system.

Due to the interdisciplinary nature of teams, communication is key.

I can help you in building this team. We start by setting reasonable goals for the project and determine the resources needed. From initial models, I then assess possible next steps including gathering and labeling more data, cleaning data, extending models, and improving computational efficiency. More resources (human or computer) may be needed as the project progresses.