Associate Machine Learning Engineer Resume

Starting...

Associate Machine Learning Engineer Resume Timothy York Associate Machine Learning Engineer (614) 555-0187 timothy.york.ml@example.com linkedin.com/example/timothyyork Columbus, Ohio 43215 STRENGTHS Trust and safety judgment During policy reviews, translated uncertain signals into testable labels and safer thresholds; partners became a go-to sounding board. Evidence-led evaluation Built error reviews around human labels and calibration checks; one careful comparison prevented an unsupported production launch. Cross-functional clarity Explained model tradeoffs in plain language for policy and product partners, earning confidence during staged deployment decisions. Practical GenAI design Tested retrieval, citations, prompts, and guardrails in a reviewer workflow; useful limits mattered as much as useful output. Reliable delivery habits Versioned datasets, documented experiments, and monitored drift across releases; teammates relied on clean handoffs when pressure rose. SKILLS Machine learning Python PyTorch TensorFlow SQL NLP Model evaluation GenAI workflows LLM orchestration Data exploration ML pipelines Cross-functional work Model monitoring Responsible AI Technical documentation LANGUAGES English Native 40 Spanish Intermediate 20 MY CAREER 3.8 Years Machine Learning Engineer at SignalHarbor Labs (1.7 Years) Machine Learning Engineer at CivicPattern Analytics (1.4 Years) Data Science Analyst at BlueOak Data Cooperative (9 Months) SUMMARY Associate Machine Learning Engineer with nearly four years applying Python, PyTorch, TensorFlow, SQL, NLP, and model evaluation methods across trust and safety, content quality, and data products. Builds reproducible ML pipelines , monitoring dashboards, and human-in-the-loop review tools that help policy specialists identify risky activity consistently. Explores LLM and GenAI workflows using retrieval, structured prompts, guardrails, and multi-step orchestration, with close attention to transparency, auditability, and responsible AI. Converts experiments into clear documentation for engineering, data science , policy, and product partners. Brings practical judgment, steady communication, and genuine interest in making digital communities safer and more inclusive. EXPERIENCE Machine Learning Engineer SignalHarbor Labs January 2025 - Present Columbus, Ohio Owns trust and safety ML initiatives spanning text classification, ranking, monitoring, GenAI review support, and audit-ready delivery. Partners with policy, product, data science, and engineering groups across production workflows. Built PyTorch classifiers for spam and harassment signals across 18 million weekly records. Created Python and SQL feature pipelines with validation, versioning, and reproducible training workflows. Developed monitoring views for precision, recall, drift, review volume, and threshold changes. Prototyped retrieval-augmented GenAI support with citations, prompt controls, and restricted-action guardrails. Compared PyTorch and TensorFlow experiments against human labels for safer operating thresholds. Documented model cards , experiment decisions, limitations, and audit artifacts for cross-functional handoffs Machine Learning Engineer CivicPattern Analytics July 2023 - December 2024 Raleigh, North Carolina Delivered NLP and data science solutions for digital community services, guiding model evaluation , scheduled scoring, compliance reporting, and staged deployment decisions. Worked closely with policy analysts and technical stakeholders. Implemented Python NLP pipelines that routed high-risk user reports into specialized review queues. Consolidated event, text, and reviewer data with SQL, pandas, provenance, and privacy controls. Evaluated TensorFlow and PyTorch baselines using confusion matrices, calibration, and stratified validation. Automated scheduled scoring and performance reporting for weekly quality and compliance reviews. Translated ambiguous policy guidance into labeled examples, escalation rules, and acceptance criteria. Presented residual risks and model tradeoffs, supporting a staged deployment decision Data Science Analyst BlueOak Data Cooperative September 2022 - June 2023 Durham, North Carolina Supported supervised learning studies through data preparation, exploratory NLP analysis, baseline modeling, reviewer tooling, and responsible-use assessment. Maintained clear records that helped senior scientists move from inquiry toward reliable evaluation. Prepared customer-support datasets with SQL and Python for supervised learning studies. Built exploratory notebooks that surfaced abuse-report language patterns for NLP feature design. Compared logistic regression, tree models, and TensorFlow text models with precision , recall , and F1. Created a human-in-the-loop labeling interface for rationale and disagreement capture. Tested prompt-based LLM classification against rules, documenting bias and reproducibility concerns. Maintained data dictionaries, experiment notes, and deployment-readiness checklists for auditability PROJECTS Policy Evidence Copilot 2025 A useful safety tool does more than produce an answer. It shows its evidence. Built a retrieval-augmented workflow that assembled policy passages, cited sources, applied guardrails, and routed uncertain cases for human review. Risk Signal Evaluation Lab 2024 Better moderation starts with better questions. Created a reproducible evaluation environment for NLP classifiers, threshold studies, calibration checks, confusion analysis, and reviewer-capacity scenarios. LEADERSHIP & AWARDS SignalHarbor Labs Responsible AI Recognition, 2025; honored for practical audit documentation and safer GenAI review workflows. CivicPattern Analytics Delivery Award, 2024; recognized for turning ambiguous policy guidance into usable evaluation criteria. North Carolina State University Computer Science Leadership Award, 2022; celebrated peer mentoring and applied ML work. EDUCATION Bachelor's Degree in Computer Science North Carolina State University GPA: 3.7 2022 Raleigh, North Carolina Coursework: Machine Learning, Natural Language Processing, Database Systems, Software Engineering, Data Mining CERTIFICATIONS Google Advanced Data Analytics Professional Certificate 2023 AWS Academy Machine Learning Foundations 2024 Responsible AI Practices, Microsoft Learn 2024 TECHNICAL SKILLS Programming Languages: Python, SQL, Bash Machine Learning Frameworks: PyTorch, TensorFlow, scikit-learn Data Analysis Tools: pandas, Jupyter, NumPy NLP Methods: Text classification, ranking, tokenization GenAI Systems: LLMs, retrieval-augmented generation, prompt evaluation ML Operations: ML pipelines, model deployment, scheduled scoring Model Monitoring: Precision, recall, class drift Data Engineering: Feature engineering, dataset validation, data versioning Responsible AI: Guardrails, bias review, human-in-the-loop Documentation Standards: Model cards, audit artifacts, data dictionaries Cloud And Containers: AWS, Docker, AWS Machine Learning Foundations Development Tools: Git, REST APIs, modular components SKILLS Machine learning Python PyTorch TensorFlow SQL NLP Model evaluation GenAI workflows LLM orchestration Data exploration ML pipelines Cross-functional work Model monitoring Responsible AI Technical documentation PROFESSIONAL AFFILIATIONS Association for Computing Machinery member; contributes thoughtful ML practice and peer exchange. Partnership on AI community participant; supports responsible AI, transparency, and inclusive technology discussions. LANGUAGES English (Native) Spanish (Intermediate) ADDITIONAL INFORMATION Work Status : Authorized to work in United States. No sponsorship required. ADDITIONAL INFORMATION Work Status : Authorized to work in United States. No sponsorship required. REFERENCES AVAILABLE ON REQUEST

File
- Open
- Save
- Save As
- Rename
- PDF Page Setup
- Preview
- PDF Download
- Show Styles
Preview
Show Styles
PDF Download
US English
US English
UK English
Spanish (LatAm)
French
German
Japanese
Italian
Portuguese (BR)
Chinese (Simplified)
Log In