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Vetted Decision Trees Professionals

Pre-screened and vetted.

JW

Principal/Senior Architect specializing in AI platforms and cybersecurity

Palo Alto, CA31y exp
ApplePeking University
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SG

Mid-level AI/ML Engineer specializing in LLM training, RAG, and scalable inference

Bay Area, CA3y exp
OpenAICarnegie Mellon University
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PN

Mid-level AI/ML Engineer specializing in LLM optimization and real-time fraud/risk modeling

St. Louis, MO6y exp
AnthropicSaint Louis University

ML engineer with 5 years at Stripe building and productionizing real-time fraud detection at massive scale (3M+ transactions/day; $5B+ annual payment volume). Delivered measurable impact (22% accuracy lift, 18% loss reduction, +3–5% authorization rates) and has strong MLOps/orchestration experience (Docker, Kubernetes, Airflow, MLflow, CI/CD, monitoring/rollback) plus a structured approach to LLM agent/RAG evaluation.

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JM

Mid-level AI/ML Engineer specializing in LLM training, RAG, and scalable inference

Bay Area, CA5y exp
OpenAICalifornia State University, East Bay
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JM

Mid-level AI/ML Engineer specializing in LLM fine-tuning, RAG, and scalable inference

Bay Area, CA5y exp
MetaSoutheast Missouri State University

ML/LLM engineer who built and shipped an LLM-powered internal knowledge assistant at Meta, focusing on production-grade RAG to reduce hallucinations and improve trust. Deep experience with scaling and serving (FSDP/DeepSpeed/LoRA, Triton, Kubernetes autoscaling) and reliability practices (Airflow retraining, MLflow versioning, monitoring with rollback), including sub-100ms latency and ~35% GPU memory reduction.

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VK

Mid-level AI/ML Engineer specializing in LLMs, RAG, and scalable MLOps

Cupertino, CA5y exp
OpenAIUniversity of North Carolina at Charlotte
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NV

Senior AI/ML Engineer specializing in LLM agents, RAG, and production ML systems

San Francisco, CA7y exp
OpenAISaint Louis University
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DN

David Neiman

Screened

Mid-level Robotics Researcher specializing in motion planning and vehicle routing

13y exp
Carnegie Mellon UniversityCarnegie Mellon University

CMU robotics PhD/PhD researcher and former CMU Robotics Club project lead who built a novel Bayes-filter-based system to localize within music so robotic instruments can follow a human’s tempo in real time. Also works on simulation-heavy multi-agent vehicle routing with traffic-signal scheduling, optimizing for real-time performance via profiling, multithreading, and neural-network surrogates for signal control.

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NK

Noelle Keto

Screened

Intern/Student Software Engineer specializing in full-stack development, AI/ML, and quantitative finance

Cambridge, MA0y exp
BarclaysHarvard University

Software engineering intern who built an internal AI-agent automation using the Gemini API to reduce manual CRM data entry, iterating prompts closely with analysts to address precision concerns. Also worked on a medical image-diagnostics LLM project involving fine-tuning and benchmarking multiple model approaches, and has quant/sales-trading experience building automated pricers for complex options and persuading sales teams to adopt them with ROI-focused metrics.

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JS

Senior Strategy & Analytics Lead specializing in AI, media, and sports analytics

6y exp
Scale AIMIT Sloan School of Management

Chief of Staff to the COO / Strategy & Business Development leader at Annapurna who unified four distinct entertainment verticals (film, TV, interactive, theatre) into the company’s first cross-functional five-year plan. Built standardized pipeline reporting, forecasting models grounded in real execution rates, and executive dashboards that improved decision-making speed and COO leverage while navigating creative/finance tension and sensitive information.

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JR

Director-level Data Architecture & Governance leader specializing in cloud analytics platforms

Los Angeles, CA16y exp
Sony PicturesUC Berkeley

Technology/architecture leader with Accenture experience delivering data- and AI/ML-driven products, including a legal contract search solution and customer sales analytics for AWS. Known for scaling distributed teams (onshore/offshore), making pragmatic architecture decisions, and solving hard data problems (proprietary sources, data quality) while implementing scalable integrations like Redshift-to-Salesforce via parallelized pipelines.

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YG

Intern Software Engineer specializing in AI agents, RAG, and full-stack web development

Pittsburgh, PA1y exp
AmazonCarnegie Mellon University
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MJ

Senior Data Scientist specializing in NLP, LLMs, and Generative AI automation

Waterford, MI12y exp
AbridgeUniversity of Georgia
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VK

Mid-level AI/ML Engineer specializing in LLMs, RAG, and MLOps

CA6y exp
MetaSaint Louis University
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JT

Intern Software Engineer specializing in data engineering and LLM evaluation

Seattle, WA1y exp
AmazonUC Berkeley
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KG

Mid-level AI/ML Engineer specializing in LLM fine-tuning, RAG, and MLOps

Bay Area, CA5y exp
MicrosoftSUNY Polytechnic Institute
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JB

Principal Data Scientist specializing in AI and quantitative investment strategies

San Francisco, CA21y exp
Wells FargoHarvard University
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SS

Mid-level AI/ML Engineer specializing in LLMs, RAG, and multi-agent systems

California, USA5y exp
Google DeepMindUniversity of North Texas
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SM

Mid-level Machine Learning Engineer specializing in LLMs, RAG, and scalable GPU inference

Bay Area, CA5y exp
PerplexitySaint Louis University
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MG

Principal Machine Learning Scientist specializing in GenAI, LLMs, and RAG

Austin, TX13y exp
Season HealthGeorgia Tech
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MD

Mid-level Software Engineer specializing in backend systems and AR/VR sensor calibration

California, United States5y exp
GoogleIndiana University Bloomington
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