Hire AI developers near Washington DC or in a similar time zone
Ryan Tang
Ryan is an applied scientist who empowers businesses to unlock the full potential of data in solving intricate, complex business problems. For the past nine years, he's been dedicated to building pragmatic, data-driven solutions that blend scientific rigor with practical business insight. With experience spanning technology, real estate, and insurance industries, he's played a pivotal role in driving significant revenue growth, developing cutting-edge products, and optimizing business functions.
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Anthony Zatika
Anthony is an experienced cybersecurity engineer, full-stack software engineer, and AI architect. He holds prestigious CISSP and CySA+ certifications. His research work has been published in prestigious journals such as IEEE/ACM and USENIX. An accomplished patent holder and distinguished Delta Alpha Pi International Honor Society member at Johns Hopkins University, Anthony is driven by innovation, adaptability, and technical precision.
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Vishnu Anurag Thonukunoori
Vishnu is an AI/ML engineer with 5+ years of experience building scalable machine learning and generative AI solutions for enterprises. He specializes in LLMs, RAG pipelines, and AWS-based deployments and has had proven success in NLP, prompt engineering, and vector search. Vishnu is trusted by clients across insurance, eCommerce, and sustainability sectors for delivering production-grade AI systems that drive business value.
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Matthew Angelini
Matthew has over a decade of experience working with startups and enterprise clients. He helps mentor, grow, architect, and develop scalable products and solutions. Matthew is an experienced engineer passionate about application development, clean user experience, consistency, and reliability.
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Igor Stankevich
Igor is a results-driven quantitative development professional with progressive industry experience in commodities, deep learning, computer vision, and data science. He has demonstrated hands-on financial and AI software development experience with in-depth knowledge of Python. Igor consistently attempts to find the best value-add opportunities and contribute to the team as a whole.
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Parham Hamouni
Parham is a senior LLM engineer and PhD researcher with 6+ years of shipping production AI systems across manufacturing, legal, and finance. At Toronto Metropolitan University, his PhD applies DPO and RLHF to temporal graph reasoning, achieving 83% pairwise accuracy and outperforming baselines by 12–15pp. In production, Parham works with RAG pipelines, fine-tuned transformers (FinBERT, Qwen, LLaMA-2), and full MLOps stacks. At Kraft Heinz, his RAG system cut troubleshooting time by 30%.
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Glenn D. House Sr.
Glenn is an AI and cloud technology executive with experience in turning emerging technologies into enterprise-scale transformations. Certified AWS-AI lead with deep expertise in GenAI, LLMs, and decision-intelligence, he delivers measurable outcomes, accelerates forecasting accuracy, and improves strategy across defense and commercial markets. Glenn is an entrepreneurial strategist with three successful startup exits who aligns AI innovation with C-suite priorities and drives AI adoption.
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Will Gao
Will is an experienced AI and machine learning architect and engineer with seven years of expertise designing, implementing, and deploying data- and AI-driven solutions. Skilled at framing generative AI and machine learning projects across diverse industries, he excels at architecting production systems and improving product and engineering alignment. As a systems thinker, Will has successfully led a consulting practice to deliver impactful results.
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Johnmicah Potter
Johnmicah is a principal-level engineer and AI architect with nearly 20 years of experience building large-scale systems for Fortune 500 enterprises and high-growth startups. Anthropic-trained, he ships production agentic AI: multi-agent systems, LLM services, and MCP servers, plus the infrastructure behind them. He founded Integrally's engineering org from zero, holds a granted patent for an AI code-generation process, and has a second AI-agent patent pending.
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Pedro Henrique Rocha Moy
Pedro is a technical leader in data science and engineering with experience building data pipelines and ML/AI systems focused on governance and accountability. He delivers impact through agentic solutions that combine domain expertise, agent design, and data and RAG pipelines to transform requirements into consistent, verifiable, and accurate DE/DS/AI systems. Pedro is experienced in agentic development, full-stack prototypes, and products agnostic to stack and cloud at any scale.
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Charles Camp
Charles is a principal AI architect and AWS Solutions Architect Associate with 10 years of experience delivering secure, production-grade AI for regulated industries. An ex–Credit Suisse AVP and Carnegie Mellon scholar, he specializes in private RAG, agentic workflows, and data-sovereign infrastructure. He has delivered high-impact solutions, including AML systems that cut false positives by 80% and legal platforms that draft complex briefs in under two minutes, operating on ET.
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