Oct 2025 – Present · 7 mos · New York City Metropolitan Area · Hybrid

• Building AI-powered fintech solutions with Flutter, Java, and ML. Led development of intelligent expense tracking (94% accuracy), real-time financial insights dashboard, and AI-driven fraud detection systems.

Jul 2025 – Oct 2025 · 3 mos · New York City Metropolitan Area · Hybrid

• Trading apps often feel overwhelming - too many numbers, too little clarity. My goal was to simplify complex flows, reduce cognitive load, and design an experience that feels fast, calm, and trustworthy. Focused on usability, real trader pain points, and clean decision-first design throughout the product.

Apr 2025 – Jun 2025 · 2 mos · Florida, United States · Remote

• Engineered custom SLM for real-time fraud detection, improving threat detection by 60% and conversion by 22% while preventing $2M+ losses. Optimized to handle 1M+ daily transactions at sub-50ms latency.

Jan 2025 – Mar 2025 · 2 mos · San Francisco Bay Area · Remote

• Architected GNN mapping financial relationships, improving credit prediction accuracy by 30%. Built Predictive ICP Engine identifying top 5% prospects, increasing Sales-Qualified Leads by 15% and customer retention by 12%.

Oct 2024 – Dec 2024 · 2 mos · New York, United States · Remote

• Developed multi-agentic system automating asset rebalancing and content generation for 10k+ institutional clients, reducing production costs by 80% while informing $10M+ GTM strategy through RAG-based intelligence.

Jul 2024 – Sep 2024 · 2 mos · Greater Seattle Area · Remote

• Built a surveillance SLM and GAN-based video generator, advancing real-time threat detection by 60% and reducing false alerts by 45%.

Apr 2024 – Nov 2025 · 1 yr 7 mos · California, United States · Remote

• Developed sophisticated AI pipelines for drug-target prediction and molecular simulations, accelerating discovery timelines by 40% using multi-omics analysis.

Jan 2024 – Jun 2024 · 5 mos · San Francisco Bay Area · Remote

• Led multi-omics AI research, boosting oncology model performance by 40% and enabling secure, cross-institutional genomic insights via federated learning.

Aug 2023 – Dec 2023 · 4 mos · San Francisco Bay Area · Remote

• Built multi-modal AI engine and LLM-BioBERT pipeline, accelerating drug discovery by 50% and enhancing target identification accuracy by 35%.

Feb 2023 – Jul 2023 · 5 mos · San Francisco Bay Area · Remote

• Designed transformer and GNN models for genomics, boosting disease classification accuracy by 30% and accelerating biomarker discovery by 40%.

Dec 2022 – Jan 2023 · 1 mo · Florida, United States · Remote

• Created AI-powered platform letting non-technical users build and deploy web or Mobile apps via simple prompts. Generated 10K+ applications. Users launched startups 90% faster than traditional development.

Oct 2022 – Nov 2022 · 1 mo · San Francisco Bay Area · Remote

• Developed ML models using SMILES embeddings for toxicity prediction, improving QSAR accuracy by 18% and automating 90% of compound screening.

Apr 2022 – Sep 2022 · 5 mos · San Francisco Bay Area · Remote

• Built GNN models and pipelines for biomarker discovery, refining binding accuracy by 15% and reducing analysis time.

Jan 2022 – Mar 2022 · 2 mos · Greater Seattle Area · Remote

• Engineered GNN-based supplier risk mapping and invoice discounting engine using alternative data signals, increasing platform transaction volume by 35% and reducing supply chain disruption costs by 15%.

Oct 2021 – Dec 2021 · 2 mos · New York, United States · Remote

• Built agentic AI systems automating lead qualification, content personalization, and due diligence, increasing email engagement by 48% while cutting partnership cycles by 67%.

May 2020 – Sep 2021 · 1 yr 4 mos · California, United States · Remote

• Directed AI strategy for next-generation language models and agentic systems, implementing MoE architectures and orchestration frameworks that automated 70% of workflows, saving $3M+ annually.

Jan 2019 – Apr 2020 · 1 yr 3 mos · California, United States · Remote

• Led advanced SLM architecture and multi-agent systems using LangChain, pioneering optimization strategies (GPTQ, LoRA, pruning) that reduced deployment costs by 65% across 2M+ daily inferences.

Jan 2018 – Dec 2018 · 11 mos · California, United States · Remote

• Deployed custom SLMs and production RAG systems processing 500K+ daily queries, implementing 8-bit quantization and knowledge distillation that reduced inference costs by 40%.

Jul 2017 – Dec 2017 · 5 mos · California, United States · Remote

• Supported development of Small Language Models and RAG pipelines, implementing quantization and pruning experiments that achieved 2-3x inference speedups on initial production benchmarks.