Garrick P.
Machine Learning & Artificial Intelligence Researcher @Algoverse
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WORK HISTORY
Machine Learning & Artificial Intelligence Researcher @Algoverse
Developed fine-tuning workflows and evaluation harnesses for large models, including latency-aware, streaming-compatible architectures applicable to speech and multimodal inference on embedded compute.• Prototyped real-time multimodal routing (audio/text) → agent reasoning → expressive response generation aligned with embodied AI requirements.• Led applied research on hallucination reduction, deterministic output, and latency optimization for enterprise-scale reasoning systems.• Architected multi-agent, workflow-aware AI systems integrating retrieval, evaluation, and orchestration layers in Python, TypeScript, and C++.• Applied Jacobian Optimization to TCP-DI to achieve 100% coverage; research under development and review.• Collaborated with research fellows on building research around agentic frameworks, builds and techniques to deliver reliability and performance.
EDUCATION
Hult International Business School
Master of Business Analytics, Business Analytics
Hult International Business School
Master of Business Administration - MBA, Management Consulting And Strategy
Universidad de Guanajuato
Spanish Language and Literature
Southwestern University
Bachelor of Arts, Communication Studies
SKILLS
ABOUT GARRICK P.
AI/ML-native engineering leader with 15+ years of experience architecting intelligent systems across analytics, backend infrastructure, and financial decision platforms. I specialize in turning ambiguity into deterministic pipelines, optimizing signal flow, and accelerating strategic decisions through structured reasoning.Class of 2025 graduate from Hult’s globally ranked, triple-crown-accredited dual master’s program (MBA + MSBA), with a specialization in Strategy & Management Consulting and a deep technical focus in Business Analytics. My academic arc includes 91+ course completion certifications across 16 frontier technologies spanning AI, ML, and data engineering, cloud architecture, quantitative finance, and applied experimentation.Builder of curated analysis pipelines and valuation frameworks capable of identifying high-leverage data, informing product direction, and enabling real-time decision systems. Fluent in Python, SQL, R, Javacript, TypeScript, C++ and the invisible subtext to architecture terrain of systems. At ease with complexity, tuned for high signal density, and committed to building infrastructure that compounds.I operate with rigor, clarity, and long-horizon thinking. I thrive in environments where intelligence, architecture, and impact converge. I keep the team engage with my hand wavy explanations while quietly estimating gradients, Jacobians, and optimization loops like the human calculus meme but in person. Skills:🧠 AI & Machine Learning Engineering - Supervised & Unsupervised Learning - Feature Engineering & Model Optimization - Evaluation Metrics & Confusion Matrix Interpretation - Python, scikit-learn, PyTorch, MLflow, DVC- Mathematically Fluent Statistical Modeling & Hypothesis Testing - Regression, Classification, Clustering, Forecasting - Time Series, A/B Testing, Hypothesis Testing - Exploratory, Descriptive, and Prescriptive Analytics Cloud Architecture & Data Pipelines - AWS, Azure, GCP, Serverless Infrastructure - ETL, Docker, Kubernetes, Airflow, Great Expectations, Data Lakes Data Strategy & Optimization - Insight Pipeline Design - Data Valuation across RAG & LLM Workflows - Time-to-Model-Quality Optimization - EVALS & Evaluation Harnesses Stakeholder Communication & Impact - Executive-Grade Storytelling - Cross-Functional Influence - Dashboarding: Power BI, Tableau - Visual Narrative Design
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