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M

Miles F.

Full-Stack Senior Engineer and AI Evaluation, Upwork & Toptal (Freelance) (01/2021–Present)

USA flagVirginia, Usa

Key Skills

Software

CloudFactoryCloudFactory
ClickworkerClickworker
Data Annotation TechData Annotation Tech
LabelboxLabelbox
MercorMercor
Micro1
OneFormaOneForma
RemotasksRemotasks
Scale AIScale AI
SuperAnnotateSuperAnnotate
Snorkel AISnorkel AI
TolokaToloka
TelusTelus

Top Subject Matter

AI code model evaluation
Benchmarking Domain Expertise
and stress testing for code generation systems

Top Data Types

ImageImage
Computer Code ProgrammingComputer Code Programming
TextText

Top Task Types

Computer Programming/CodingComputer Programming/Coding
Data CollectionData Collection
Evaluation/RatingEvaluation/Rating
Text SummarizationText Summarization
Question AnsweringQuestion Answering
Text GenerationText Generation
Object DetectionObject Detection
ClassificationClassification
SegmentationSegmentation
Point/Key PointPoint/Key Point
Fine-tuningFine-tuning

Freelancer Overview

Full-Stack Senior Engineer and AI Evaluation, Upwork & Toptal (Freelance) (01/2021–Present). Brings 6+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Internal and Proprietary Tooling. Education includes Doctor of Philosophy, University of Texas at Austin (2023) and Master of Science, Rice University (2018). AI-training focus includes data types such as Computer Code and Programming and labeling workflows including Evaluation and Rating.

Labeling Experience

Full-Stack Senior Engineer and AI Evaluation, Upwork & Toptal (Freelance) (01/2021–Present)

Built fully automated assessment systems to evaluate the accuracy and quality of AI code models at scale. Implemented CI/CD with in-between model testing to support reproducible research workflows and continuous evaluation. Developed infrastructure and distributed evaluation pipelines to stress-test AI-assisted codification and measure performance metrics. • Scaled benchmarking pipelines to handle millions of generated code outputs • Created full-stack dashboards to visualize AI performance metrics and error patterns • Implemented distributed evaluation using Docker and Kubernetes clusters • Built safe APIs and back-end services for large-scale experimentation pipelines

2021 - Present

Doctor of Philosophy (PhD), Computer Science - AI Systems, University of Texas at Austin (09/2019–12/2023)

Researched and developed evaluation frameworks for AI-assisted code generation with a focus on reliability. Authored peer-reviewed work on benchmarking and evaluation systems to advance standardized methods for assessing model performance. Conducted large-scale experimentation and analysis aligned with distributed systems and software engineering evaluation. • Developed evaluation frameworks for AI-assisted code generation reliability • Authored benchmarking and evaluation papers presented at NeurIPS and ICLR • Collaborated with Microsoft Research and academic partners on evaluation efforts • Supported teaching as a teaching assistant while continuing evaluation research

2019 - 2023

Education

U

University of Texas at Austin

Doctor of Philosophy, Computer Science

Doctor of Philosophy
2019 - 2023
R

Rice University

Master of Science, Computer Science

Master of Science
2014 - 2018

Work History

T

Toptal

Full-Stack Engineer and AI Evaluation Specialist (Freelance)

New York
2021 - Present
U

Upwork

Full-Stack Senior Engineer and AI Evaluation Specialist

New York
2021 - Present