Raga Markely
Principal Machine Learning Engineer at Grab
Washington, Singapore
Summary
👤
Senior🎓
Top SchoolRaga Markely is a Principal Machine Learning Engineer with eight years of experience applying reinforcement learning, gradient-boosted trees, and gradient-free optimization to improve large-scale production systems. Trained as a chemical engineer and applied mathematician with a PhD from MIT, he blends rigorous mathematical modeling with practical ML engineering to deliver measurable reliability and efficiency gains across marketplaces and infrastructure. At Meta he partnered closely with FAIR and software teams to operationalize complex models, and at Grab he built a custom simulator and deep RL agent to optimize two-sided marketplace dynamics. Earlier roles in biopharma and academia demonstrate his ability to lead cross-functional programs—linking regulatory, operations, and research stakeholders—to deploy compliant, optimized supply chains and analytical methods. He is comfortable moving ideas from theorem-proof and lab work to production-grade systems, a skillset that underpins his rare mix of domain depth and production impact.
9 years of coding experience
20 years of employment as a software developer
Doctor of Philosophy (Ph.D.) Chemical Engineering, Doctor of Philosophy (Ph.D.) Chemical Engineering at Massachusetts Institute of TechnologyBachelor of Science - BS Chemical Engineering (minor in Applied Mathematics), Bachelor of Science - BS Chemical Engineering (minor in Applied Mathematics) at University of Wisconsin-Madison
English, Indonesian
Github Skills (3)
mixed-integer-programming10
python9
vehicle-routing-problem9
Programming languages (2)
Github contributions (5)
ragamarkely/scanalytics
Jul 2017 - Feb 2021
Python implementation to solve Vehicle Routing problem & Master Production Scheduling in Supply Chain Analytics & Design.
Contributions:55 commits, 22 pushes, 1 branch in 3 years 7 months
pythonvehicle-routing-problemsupply-chain-analyticsmixed-integer-programming
ragamarkely/enron_fraud
Jul 2017 - Sep 2017
Contributions:150 commits, 94 pushes, 1 branch in 2 months
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