I love cracking hard problems. Whether you're building something ambitious, stuck on a technical direction, or just want to explore ideas—let's talk about it. 10+ years in production ML, across finance, automotive, vision, and deep tech.
What's the challenge you're facing? What are you trying to build? Let's understand it deeply and figure out the best approach.
I love the creative problem-solving part. That moment where we take something that seems impossible and figure out the angle. The intersection of deep technical thinking and scrappy iteration. Building solutions that work.
Let's start there. Understanding your situation, exploring solutions, and building something great together.
Here are the different ways we might work together. The right approach depends on your situation.
Full ownership of your technology. Architecture decisions, team management, product development, and investor-ready technical documentation. I build it, run it, and hand it over.
Embedded ML lead on your team. Technical roadmap, model development, data infrastructure, team building. Strategic thinking with hands-on execution.
Let's understand your challenge deeply. What are you trying to solve? What's feasible? What's the creative angle? A focused exploration leading to a clear roadmap.
End-to-end ML solutions from ideation to production. Custom models, data pipelines, infrastructure. I write the code, think through the architecture, and make sure it actually works.
Building your first technical team. Finding the right people, defining roles, evaluating candidates, onboarding, and creating an environment where they can do their best work.
Self-hosted LLM deployments, privacy-preserving AI systems, custom GPU infrastructure. For companies that need AI without compromising data security.
End-to-end ownership — from research and architecture to production deployment and team building.
Cross-domain experience means I see patterns and solutions that specialists miss.
I'm a machine learning engineer and technical leader with a background in theoretical physics. I started in academic research (PhD at the University of Groningen, Master's in Mathematics at Cambridge), then spent a decade building production ML systems in industry.
My career has taken me from quantitative finance at ING, to HD maps for self-driving cars at TomTom, to leading a computer vision team at Huawei's R&D center in Amsterdam. Along the way I've been interim lead data science for a medical diagnostics startup and developed ML solutions for engineering, marketing, and tourism.
What I bring is rare combination: I can design a neural network architecture, set up the GPU infrastructure to train it, build the production API to serve it, and explain it to investors. I write the code myself, then build the team to maintain it.
I also run Data Driven Lab Consulting — applying ML and automation to analytical chemistry and materials science R&D. And I write about ML, data science, and software engineering at sjoerddehaan.com.
Go Grow AI B.V.
Go Grow AI — ML/AI consulting (general)
Data Driven Lab Consulting — Science & engineering
Turnerstraat 27D
1076 VC Amsterdam
83138218
NL862745809B01
sjoerd@gogrowai.com
+31 6 12261747
Tell me about your challenge. Whether it's technical direction, building something ambitious, or exploring what's possible—let's dig in.