Eliminate Engineering Bottlenecks that Slow Scientific Discovery

Unlock scientific breakthroughs by eliminating bottlenecks at the intersection of Software Engineering, AI, ML, and Research. Enable teams to run 20X more experiments, reduce time-to-insights by months, and strengthen team productivity.

With 25 years of experience, I simplify complex architectures, streamline cloud adoption, and empower science teams to scale their research capabilities and accelerate the path from discovery to impact.

Common Challenges in Research Software

Even the best research teams can face barriers that slow progress. Some patterns that often appear include:

  • Legacy systems that limit throughput: growing datasets overwhelm infrastructure, slowing research progress.

  • Unreliable results from data pipelines: errors and inconsistencies in data handling lead to unpredictable ML or research outcomes.

  • Technical debt and system complexity: outdated or patchwork systems add friction to R&D and make innovation harder to sustain.

  • Collaboration bottlenecks: misalignment between scientists and engineers extends development cycles and delays breakthroughs.

How I Can Help
I work with research teams to modernize their software and data infrastructure so they can focus on discovery, not debugging. My services include leveraging AI for research, building scalable data pipelines, simplifying complex systems, and improving collaboration between scientists and engineers, all with the goal of removing bottlenecks that slow down innovation.

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My name is Carlos Garcia Jurado Suarez, and I’m a Software and Machine Learning Engineering Consultant helping research organizations.

I have over 25 years of experience as an engineer, applied scientist, and manager at organizations of all sizes: Big Tech (Microsoft Research, Meta), early and growth stage startups and academia. My expertise and passion are in Machine Learning and Scientific Computing, and in particular bridging the research and engineering worlds.

I hold master's degrees in Computer Science and in Applied Mathematics, both from the University of Washington, as well as a bachelor's degree in Physics from ITESM, in Monterrey, Mexico.

11 Patents
10 Software Products
Academic Publications

Organizations I've Helped

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“Carlos is one of the most disciplined and skilled software engineers/architects I’ve encountered in my 30 year career. His deep intellectual curiosity and engineering craftsmanship have bestowed his teams with engineering designs & implementations that have stood the test of time, always conscious of performance, scalability and extensibility. ”
Gavin Janke, Microsoft Research

Carlos helped me with setting up my AI start-up. We had many consultations as I took my idea from concept to a fully functioning app that serves a niche. Carlos's perspective was invaluable at pointing out potential markets and use cases for my product. Every call with Carlos, I was surprised at how many ideas we came up with together. He helped me with his personal expertise, but also helped develop my capabilities as an entrepreneur.

I highly recommend speaking to Carlos if you have the opportunity. I really value our consultations and look forward to continuing to share with him in the future.

Mike Gallagher, Engineering Manager at Depop; Founder at tokencrush.ai
Carlos is a seasoned machine learning engineer who embodies the role almost perfectly. He has deep expertise in machine learning, having worked in research and product ML teams. He is also a fantastic software engineer who writes high-quality and well-designed code. On top of that, he was a caring manager who put his team first and led through ambiguity. Carlos’s decorated career speaks for itself, but it’s the human touch in all interactions with him that one remembers having worked with him. He will be an asset to any project or team as he can drive through tough situations and focus on impact.
Kushal Lakhotia, Meta / Outreach
I had the pleasure of working with Carlos as my manager at Microsoft Research, and it was one of the highlights of my career. He was instrumental in creating an environment where the team felt valued and empowered to do their best work. When I recently had the chance to work with Carlos again at an ML startup, it was a major reason for me to join the team. I knew I'd be working with someone I could trust—a highly capable leader who is ego-free and always willing to help. Carlos is a true force multiplier. He's someone who proactively builds tools that nobody asks for but that make everyone's jobs a little bit easier. I highly recommend working with Carlos if you get the chance.”
Johan Verwey, Irreverent Labs/ Microsoft Research
I first worked with Carlos at Meta, where I was impressed by his technical depth and leadership. When the opportunity arose at Outreach, I knew he would be the right person to build and lead our Machine Learning team from the ground up, so I brought him on board. Carlos is a rare combination of a strong ML scientist and a seasoned backend engineer. He can design and implement complex systems end-to-end, while also applying cutting-edge machine learning techniques to deliver real impact. At Outreach, we worked as peer Directors, and I consistently saw how he raised the technical bar, built trust across teams, and delivered results that moved the business forward. Carlos is one of the most capable and versatile engineering leaders I’ve worked with, and any organization would be fortunate to work with him.
Guowei Shieh, Meta / Outreach
“I met Carlos at Microsoft Research and was impressed by his quest for knowledge. He has the skills for both engineering and research and can be relied upon to deliver on time with high quality. He is committed to excellence, is a good listener and a great colleague. ”
Nirupama Chandrasekaran, Microsoft Research

    Software Engineering Blog: Learn To Maximize Results

    I've written a series of articles on how to become better software engineers. From individual skills to better team practices, learn about how deliver better results.


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