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I'm a Senior Machine Learning Engineer with 8+ years of experience building scalable AI systems, evaluation pipelines, anomaly detection workflows, experimentation platforms, and internal tooling across leading tech organizations such as Meta and Microsoft. I focus on turning complex data problems into reliable, production-ready solutions that scale. I enjoy collaborating with product, data, and platform teams to improve measurement quality, pipeline performance, and engineering productivity, and I love enabling engineers and stakeholders to review failure context quickly and make informed product decisions.…I'm a Senior Machine Learning Engineer with 8+ years of experience building scalable AI systems, evaluation pipelines, anomaly detection workflows, experimentation platforms, and internal tooling across leading tech organizations such as Meta and Microsoft. I focus on turning complex data problems into reliable, production-ready solutions that scale. I enjoy collaborating with product, data, and platform teams to improve measurement quality, pipeline performance, and engineering productivity, and I love enabling engineers and stakeholders to review failure context quickly and make informed product decisions.

Michael Zhang

AI Engineer, Data Scientist, Full Stack Developer, +3

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I'm a Senior Machine Learning Engineer with 8+ years of experience building scalable AI systems, evaluation pipelines, anomaly detection workflows, experimentation platforms, and internal tooling across leading tech organizations such as Meta and Microsoft. I focus on turning complex data problems into reliable, production-ready solutions that scale. I enjoy collaborating with product, data, and platform teams to improve measurement quality, pipeline performance, and engineering productivity, and I love enabling engineers and stakeholders to review failure context quickly and make informed product decisions.…I'm a Senior Machine Learning Engineer with 8+ years of experience building scalable AI systems, evaluation pipelines, anomaly detection workflows, experimentation platforms, and internal tooling across leading tech organizations such as Meta and Microsoft. I focus on turning complex data problems into reliable, production-ready solutions that scale. I enjoy collaborating with product, data, and platform teams to improve measurement quality, pipeline performance, and engineering productivity, and I love enabling engineers and stakeholders to review failure context quickly and make informed product decisions.

Available to hire

I’m a Senior Machine Learning Engineer with 8+ years of experience building scalable AI systems, evaluation pipelines, anomaly detection workflows, experimentation platforms, and internal tooling across leading tech organizations such as Meta and Microsoft. I focus on turning complex data problems into reliable, production-ready solutions that scale.

I enjoy collaborating with product, data, and platform teams to improve measurement quality, pipeline performance, and engineering productivity, and I love enabling engineers and stakeholders to review failure context quickly and make informed product decisions.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Language

English

Fluent

Work Experience

Senior Machine Learning Engineer at Meta

May 1, 2024 - April 30, 2026

Led ML-focused work in Reality Labs developer infrastructure, improving test signal quality, failure analysis, and debugging support across large-scale end-to-end workflows. Built an attribution workflow combining historical feedback and heuristic ranking to improve regression identification precision and reduce noisy triage. Developed LLM-assisted workflows for diff summarization and test selection analysis to help engineers review failure context faster during debugging and release validation. Designed anomaly detection pipelines for production engineering signals, improving visibility into abnormal test and infrastructure behavior and shortening investigation time for recurring issues.

Senior Software Engineer at Microsoft

June 1, 2022 - April 30, 2024

Led development for Microsoft Data Platform initiatives and contributed to the M365 Copilot evaluation framework, delivering multiple end-to-end projects across evaluation, reporting, and platform usability. Built production-scale online and offline evaluation pipelines for Copilot and Search using LLM-assisted workflows, Spark, and large-scale data processing systems. Designed metrics pipelines and compliant scorecards for internal evaluation scenarios, balancing technical accuracy with governance and reporting requirements. Partnered with engineers, data scientists, and product stakeholders to improve experimentation workflows, reporting quality, and internal evaluation tooling across shared platform use cases. Mentored junior engineers through design reviews and onboarding support.

Software Engineer 2 at Microsoft

March 1, 2021 - June 30, 2022

Drove roadmap execution for M365 Search evaluation agility tools with a focus on faster onboarding, better diagnosis quality, and improved usability for internal users. Built an SLA dashboard for MSAI scorecards and improved engineering efficiency through tooling and workflow optimization. Expanded the MSAI Data Studio Portal with performance dashboards and stakeholder-driven enhancements. Delivered internal tools including Logging Designer, E2E Tool, Log Sampling Tool, and Data Quality Scorecard to strengthen observability and improve engineering productivity.

Software Engineer 1 at Microsoft

December 1, 2019 - March 31, 2021

Built evaluation scorecards and dashboards supporting experimentation across 20+ MSAI features, improving a more reliable measurement layer for product decisions. Improved pipeline performance and SLA by optimizing workflows and reducing end-to-end latency from 35 hours to 24 hours. Collaborated with client teams, logging teams, and data science partners to resolve data issues, improve platform quality, and close feature gaps. Supported resolution of high-severity outages and compliance-related issues affecting downstream data availability and evaluation workflows.

Machine Learning Engineer at GUANDATA

May 1, 2018 - December 31, 2019

Managed the Unilever demand forecasting solution and coordinated delivery across planning, sales, BI, and data science stakeholders. Improved forecast accuracy by 10% across 5,000+ SKUs, translating modeling work into measurable business value. Built an end-to-end forecasting platform enabling domain experts to trigger prediction runs, review results, and interpret outputs directly. Developed custom loss functions and blending strategies to improve robustness and forecasting performance under real business conditions.

Data Science Intern at Rabobank

July 1, 2017 - May 31, 2018

Investigated fraud detection problems using ML, H2O, and statistically grounded evaluation methods tailored to business constraints. Developed cluster-based modeling strategies and used PAUC to optimize performance under fixed false-positive-rate requirements. Explored concept drift detection approaches for fraud and phishing scenarios where real-time labels were limited or unavailable. Built a visualization application for domain experts, later adopted in production.

Student Assistant, Software Development at Sure Innovation

October 1, 2016 - June 30, 2017

Developed an internal platform using PHP, WordPress, and database-backed backend workflows. Designed question submission and management flows that converted a manual institutional process into a structured software-supported workflow. Contributed to backend logic, data modeling, and usability improvements for internal administrative tools.

Software Developer Intern at Lenovo

February 1, 2016 - June 30, 2016

Implemented an internal retailer platform using Java and Spring MVC for sales reporting, supply requests, and role-based workflows. Applied backend logic, access control, and enterprise web development practices in a business environment with evolving requirements.

Senior Machine Learning Engineer at Meta (Reality Labs)

May 1, 2024 - April 30, 2026

Led ML-focused work in Reality Labs developer infrastructure, building Python-based systems to improve test signal quality, failure analysis, and debugging support across large-scale end-to-end workflows. Built an attribution workflow combining historical feedback and heuristic ranking to improve regression identification precision and reduce noisy triage during investigation. Developed LLM-assisted workflows for diff summarization and test selection analysis, helping engineers review failure context faster during debugging and release validation. Designed anomaly detection pipelines for production engineering signals, improving visibility into abnormal test and infrastructure behavior and shortening investigation time for recurring issues.

Machine Learning Engineer at GUANDATA (Unilever forecasting project)

May 1, 2018 - December 31, 2019

Managed the Unilever demand forecasting solution and coordinated delivery across planning, sales, BI, and data science stakeholders. Improved forecast accuracy by 10% across 5,000+ SKUs, translating modeling work into measurable business value. Built an end-to-end forecasting platform enabling domain experts to trigger prediction runs, review results, and interpret outputs. Developed custom loss functions and blending strategies to improve robustness under real business conditions.