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Senior Machine Learning Engineer at The NetCircle in Shanghai. Currently focused on helping drive The NetCircle’s shift toward agentic, AI-native software development.
I’m a senior machine learning and systems engineer with 15+ years of experience across AI/ML, backend engineering, distributed systems, infrastructure, and technical architecture. Over the course of my career, I’ve built and operated business-critical real-time platforms, distributed messaging systems, internal ML and automation tooling, and production AI-native applications. At The NetCircle, my role has grown from being the company’s first data scientist into leading work across AI-native product development, retrieval and ranking systems, internal engineering standards for AI/automation readiness, and cross-team adoption of agentic development practices. I also have deep infrastructure experience, including long-term ownership of hardware planning and datacenter expansion, helping grow our server footprint from roughly 5 to 50 machines while balancing performance, reliability, and cost. My background combines hands-on technical depth with platform thinking: I enjoy turning complex ideas into systems that are practical, scalable, and dependable in production.
KTH Royal Institute of Technology
Computer Science
January 1, 2007 – January 1, 2010
The NetCircle
Senior Machine Learning Engineer
June 1, 2023 – Present
The NetCircle
Advanced Machine Learning Engineer
November 1, 2015 – June 1, 2023
Woohe Internet Technology Co., Ltd.
Research and Development Group Leader
March 1, 2015 – November 1, 2015
Dalian, Liaoning, China
Sigma IT & Management
Lead Developer
January 1, 2012 – February 1, 2015
Sigma IT & Management
Systems Developer
January 1, 2010 – January 1, 2012
Blockchain Platforms
Coursera
June 24, 2026 – Present
Neural Networks and Deep Learning
Coursera
June 24, 2026 – Present
The Data Scientist’s Toolbox
Coursera
June 24, 2026 – Present
Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization
Coursera
June 24, 2026 – Present
Structuring Machine Learning Projects
Coursera
June 24, 2026 – Present
Getting Started: Agile Meets Design Thinking
Coursera
June 24, 2026 – Present
Data-driven Astronomy
Coursera
June 24, 2026 – Present
Fundamentals of Scalable Data Science
Coursera
June 24, 2026 – Present
Blockchain Basics
Coursera
June 24, 2026 – Present
DeepLearning.AI TensorFlow Developer Specialization
Coursera
June 24, 2026 – Present
Applied Social Network Analysis in Python
Coursera
June 24, 2026 – Present
Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning
Coursera
June 24, 2026 – Present
Convolutional Neural Networks in TensorFlow
Coursera
June 24, 2026 – Present
Natural Language Processing in TensorFlow
Coursera
June 24, 2026 – Present
Sequences, Time Series and Prediction
Coursera
June 24, 2026 – Present
TensorFlow in Practice Specialization
Coursera
June 24, 2026 – Present
Introduction to Applied Machine Learning
Coursera
June 24, 2026 – Present
Introduction to Machine Learning in Production
Coursera
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's experience is heavily skewed towards Machine Learning Engineering, backend development, and infrastructure, with significant leadership roles. While there is some historical frontend experience (JSP, JavaScript, jQuery, CSS), their recent and primary focus is not on modern frontend development. This creates a significant mismatch with the 'Frontend Developer' target role, indicating a potential cultural fit challenge for a dedicated frontend team.
Soft Skills & Operational Fit
The candidate demonstrates strong leadership, mentoring, and project management skills. Experience in establishing data science functions and leading AI initiatives indicates a proactive and innovative mindset. Their background in DevOps and infrastructure management suggests operational readiness and a holistic understanding of system lifecycles. Agile methodology experience further supports operational fit.