Hi, I'm Pavel Shmakov - Senior Machine Learning Engineer at PhysicsX
I thrive at the intersection of theoretical physics and cutting-edge software engineering. My passion lies in leveraging complex scientific concepts to build robust, high-impact ML solutions, especially in research-driven deep tech environments.
At a glance
Curated signals on strengths, focus areas, and how they can help.
Interned at Google for 5 years, focusing on large-scale distributed systems and backend development.
Currently a Senior Machine Learning Engineer at PhysicsX, driving research in scientific computing.
Can help others by advising on scalable software architecture for scientific applications.
🚀 Career trajectory
Foundational Physics Research
Gained deep analytical and problem-solving skills through a PhD in theoretical physics.
✦ Theoretical Physics
✦ Numerical Analysis
✦ Scientific Writing
Google Software Engineering
Developed expertise in large-scale systems, distributed computing, and backend development at Google.
✦ Google Cloud Platform
✦ Distributed Systems
✦ Backend Development
Startup and Product Focus
Applied engineering skills in fast-paced startup environments and product development roles.
✦ Full Stack Engineering
✦ Startup Environments
✦ Product Development
Research-Led ML Engineering
Currently focusing on advanced machine learning and scientific computing at PhysicsX.
✦ Machine Learning
✦ Scientific Computing
✦ Research Engineering
💪🏻 Superpowers
Bridging Physics and Code
Translating complex scientific concepts into robust software solutions.
✦ Leveraged PhD in theoretical physics for advanced ML research.
✦ Applied scientific computing and numerical analysis to engineering problems.
✦ Developed ML models for scientific discovery and innovation.
Google-Scale Engineering
Proven ability to deliver complex systems in high-impact environments.
✦ Contributed to large-scale distributed systems at Google.
✦ Gained deep experience with GCP and big data technologies.
✦ Focused on code quality, testing, and technical debt reduction.
Full-Spectrum ML Expertise
From research to production, driving ML initiatives forward.
✦ Applied TensorFlow, PyTorch, and OpenAI products.
✦ Specialized in backend, GCP, and scientific computing domains.
✦ Excels in both research and product-focused ML engineering roles.
I'm excited about
✦ Exploring novel ML applications at the intersection of science and technology.
✦ Connecting with experts in cutting-edge AI and scientific research fields.
✦ Discovering opportunities for impactful research collaborations.
I can help with
✦ Providing expertise on complex machine learning model development.
✦ Advising on scalable software architecture for scientific applications.
✦ Sharing insights into high-performance computing and data processing.
I would love your help on
✦ Identifying potential collaborators in novel physics-based AI research.
✦ Finding leaders in quantum computing or advanced simulation fields.
✦ Discovering early-stage startups pushing scientific boundaries with AI.
