Hire the Best Deep Learning Experts in California

Welcome to my Upwork Profile! My name is Ethan and I am a Deep Learning Engineer whose focus is in Natural Language and Computer Vision. I enjoy developing new and novel models as well as creating infrastructure for automation and ease-of-use. Data of all types interest me. I have experience developing Deep Learning applications for a variety of hardware architectures, including mobile devices such as Nvidia Jetson, Raspberry Pi, Android, and iOS. Working with me you will get best practice in source code management, version control, and security access to your code base. Additionally, my team can provide infrastructure for training, testing, and hosting for any Deep Learning model or web-based application. My technology stack is listed in long-form below. Core: - Linux/Debian - Python 3 - Markdown - Git Data Manipulation: - Numpy - Pandas - OpenCV - PIL/Pillow Machine Learning - Scikit-learn - NLTK - dlib - xgboost Deep Learning: - Tensorflow - Keras - PyTorch Visualization: - Matplotlib - Seaborn - Bokeh - Plotly Web: - Flask - Django - OpenFaaS - Knative - Gunicorn DevOps & Orchestration: - Docker - Docker Compose - Kubernetes Thanks for your consideration!

𝐁𝐚𝐜𝐤𝐠𝐫𝐨𝐮𝐧𝐝: PhD in Theoretical Computer Science; ex-Director of ML Research at Nuro; ex-Chief Scientist at Huawei Research; 45 publications and 40 patents; area chair and reviewer at CVPR, NeurIPS, ICML, and ICLR. I've led teams of 25, but what I love is building - which is why I'm here: full-time, hands-on, writing the code myself. I build ML systems that make it to production. If your RAG pipeline hallucinates, your agents loop and burn tokens, your fine-tune won't converge, or accuracy has plateaued and nobody knows why - that's the work I do best. 𝟐𝟎 𝐲𝐞𝐚𝐫𝐬 from DSP firmware to frontier multimodal AI means I debug these systems from silicon up, not by guessing. 𝐖𝐡𝐚𝐭 𝐈 𝐁𝐮𝐢𝐥𝐝 ➤ Agentic AI: multi-agent workflows with LangGraph and OpenAI/Anthropic agent stacks - tool design, custom MCP servers, memory, guardrails, LLM-as-judge validation loops. Agents that finish the job, reliably and at predictable cost. ➤ Computer vision at extreme scale: face recognition deployed globally at Huawei; gigapixel pathology imaging; video retrieval (MDMMT, top of its benchmark); super-resolution, edge compression. ➤ RAG & LLM applications: retrieval that actually grounds its answers; multimodal RAG with Vision-Language Models (SafeAuto, ICML 2025); evaluation harnesses so quality is measured, not assumed. ➤ LLM fine-tuning & optimization: LoRA/QLoRA, quantization, distillation, synthetic data pipelines. Frontier-model quality at a cost you can afford to run. ➤ Backend & MLOps: Python/FastAPI microservices, REST APIs, Docker, CI/CD, model serving (vLLM, Triton), Postgres/Redis, vector DBs, AWS/GCP - on a systems background that goes down to flash controllers, LDPC error-correcting codes, and DSP firmware (30+ patents at LSI/Broadcom). ➤ Data science & classic ML: credit scoring, churn prediction, fraud/anomaly detection, forecasting, recommenders, A/B testing - shipped as VP of R&D at a FinTech holding. ➤ AI reliability & safety: adversarial robustness (I authored AdvHat, the widely cited real-world attack on ArcFace FaceID), certified defenses, uncertainty quantification, safe RL. I know exactly how models fail and build guardrails that hold. 𝗥𝗲𝗰𝗲𝗻𝘁 𝗣𝗿𝗼𝗷𝗲𝗰𝘁𝘀 𝗜’𝗺 𝗣𝗿𝗼𝘂𝗱 𝗢𝗳: 🏆 FinTech: as VP of R&D, built an agentic underwriting platform - LangGraph agents with custom MCP tools that read financial documents (OCR + VLM) and draft credit decisions. Manual review time dropped ~70%, and fraud recall went up 18 points without raising false positives. 🏆 Healthcare: gigapixel pathology scans, billions of pixels each. Multi-scale transformers plus an LLM that drafts the structured findings. Pathologists spend ~40% less time per case; distillation cut inference cost 5x. 🏆 Autonomous driving: prediction, diffusion-based planning, and RL motion selection at Nuro and Gatik - top places on Argoverse and Apolloscape, and SafeAuto (ICML 2025) is SOTA on driving benchmarks. 𝐖𝐡𝐞𝐫𝐞 𝐈'𝐯𝐞 𝐖𝐨𝐫𝐤𝐞𝐝 🌐 Now: VP / Head of R&D at a FinTech holding; Adjunct Professor of ML and AI at Sofia University (Palo Alto) 🌐 Head of AI at Logical Intelligence 🌐 Sr. Director of AI Research at Gatik (Silicon Valley) 🌐 Director of ML Research at Nuro (Silicon Valley) 🌐 Chief Scientist at Huawei Research 🌐 Managing Director at the Artificial Intelligence Research Institute 🌐 Senior Software Engineer at LSI (now Broadcom) - 6 years fully remote for a US company Remote, hybrid, or embedded - I've delivered in all three. 📌 I've usually already solved the harder version of your problem. I measure before I claim: every engagement ships with evaluation you can rerun yourself. Your team keeps the knowledge - I founded Nuro ML University (100+ engineers trained) and teach as I build. And I've been graded on delivery, not just papers: 𝟏𝟑 𝐜𝐨𝐫𝐩𝐨𝐫𝐚𝐭𝐞 𝐚𝐰𝐚𝐫𝐝𝐬 at 𝐇𝐮𝐚𝐰𝐞𝐢, including Excellent Delivery and Customer Success; 𝐢𝐧𝐯𝐢𝐭𝐞𝐝 𝐬𝐩𝐞𝐚𝐤𝐞𝐫 at 𝐂𝐕𝐏𝐑, 𝐀𝐀𝐀𝐈, and 𝐖𝐀𝐂𝐕 𝐰𝐨𝐫𝐤𝐬𝐡𝐨𝐩𝐬 in 2025. Short technical discovery, architecture and milestone plan, a working system early, iteration against agreed metrics (accuracy, latency, cost), then documentation and a recorded handoff. Plain-English updates, async-friendly, US and EU hours. Stack: Python, PyTorch, C++, CUDA, FastAPI, OpenAI/Anthropic APIs, LangChain/LangGraph, MCP, vLLM, Transformers, RAG, NLP, FAISS/Pinecone/Weaviate, LoRA/QLoRA, diffusion models, RL, scikit-learn, XGBoost, Docker, AWS/GCP, W&B, MLflow. Not ready for a full build? Start with a fixed-scope audit of your RAG, agent, or ML system - architecture review, evaluation gaps, and a prioritized fix list you can execute with or without me. Send me the problem - what you're building, what's failing, what "good" looks like - and I'll reply with a concrete technical assessment and a scoped plan within one business day. Alex

My interests and passion lie at the intersection of mathematics, physics and deep learning. I am interested in exploring and developing new ideas in deep and causal learning and applying them to different fields. I am also interested in developing techniques in uncertainty quantification to deep learning models, especially to generative AI models to determine how and in which cases they fail.

Expert Vetted. Stanford MS in AI. 200+ projects. 100% success rate. $1M+ delivered through Upwork. If you are building AI Agents, automating business workflows, deploying LLMs, or scaling machine learning systems, you have found the right engineer. I'm Tayyab. 10 years building production-grade AI for startups, scale-ups, and enterprises across legal, healthcare, finance, insurance, and SaaS. My work has helped clients raise $50M in funding, cut processing time by 40%, achieve 90% prediction accuracy, scale deal flow by 10x, and eliminate hundreds of hours of manual work annually. 🤖 AI Agents & Workflow Automation ▸ Multi-agent orchestration: LangGraph, CrewAI, AutoGen, OpenAI Agents SDK, Semantic Kernel ▸ n8n, Make, Zapier, Pipedream: end-to-end business process automation ▸ CRM, email, document, and reporting automation: Salesforce, HubSpot, Slack, Notion, Google Workspace ▸ Celery, Redis, Temporal: distributed workflow execution ▸ Human-in-the-loop systems, agent memory, tool use, approval workflows 🧠 Generative AI, LLMs & RAG ▸ GPT-4o/o1/o3, Claude 3.5, Gemini, Llama 3, Mistral, Qwen, HuggingFace, Groq, Ollama ▸ Enterprise RAG: Pinecone, Qdrant, Weaviate, ChromaDB, FAISS, pgvector, Neo4j ▸ Fine-tuning: QLoRA, DeepSpeed, Unsloth, LoRA on GPU clusters ▸ LangChain, LlamaIndex, LangSmith, DSPy, TextGrad, MemGPT 📊 Machine Learning & Computer Vision ▸ PyTorch, TensorFlow, Scikit-learn, XGBoost, LightGBM: classification, regression, forecasting, anomaly detection ▸ YOLO, Detectron2, OpenCV, OCR: document intelligence and visual AI ▸ Voice AI: Whisper, ElevenLabs, Retell AI, Bland AI, Twilio, LiveKit ▸ Stable Diffusion, Flux, ComfyUI: generative imaging and video ☁️ MLOps & Cloud ▸ AWS, GCP, Azure: Kubernetes, Docker, serverless ▸ MLflow, BentoML, Weights & Biases: model deployment and monitoring ▸ FastAPI, Flask, Node.js, React, PostgreSQL, MongoDB 🏆 Selected Projects ▸ Enterprise cloud cost intelligence platform: 25% cost reduction, $50M funding secured ▸ Insurance medical records pipeline: 40% faster processing, 90% cost prediction accuracy ▸ RAG-powered legal analysis system: 80% alignment with real judicial verdicts ▸ NLP contract intelligence platform: 4 hours saved per contract, 80% accuracy improvement ▸ Sustainability analytics dashboard: 130M+ tons of CO2e managed, 200+ hours saved annually ▸ ML startup evaluation engine: 10x deal flow capacity, weeks to seconds per evaluation ▸ Multi-agent lead generation system: 70% reduction in manual prospecting effort ▸ AI conversational support system: thousands of daily conversations automated across multiple channels ✅ Why Me? ▸ Stanford MS in AI: Top 1% Expert Vetted on Upwork ▸ 200+ projects, zero failed engagements, $1M+ delivered ▸ Systems that run in production, not demos that die in staging 📩 AI Agents, workflow automation, LLMs, or machine learning: let's talk. Machine Learning, Deep Learning, Generative AI, LLMs, AI Agents, Agentic AI, Multi-Agent Systems, Workflow Automation, AI Automation, LangChain, LangGraph, CrewAI, AutoGen, RAG, Retrieval-Augmented Generation, Vector Databases, Pinecone, Weaviate, FAISS, Fine-Tuning, QLoRA, Prompt Engineering, OpenAI, GPT-4, Claude, Gemini, Llama, Mistral, HuggingFace, PyTorch, TensorFlow, XGBoost, LSTM, Transformers, YOLO, OpenCV, OCR, Stable Diffusion, Voice AI, Whisper, ElevenLabs, n8n, Make, Zapier, FastAPI, Docker, Kubernetes, AWS, GCP, Azure, MLflow, MLOps, Time Series Forecasting, Anomaly Detection, Semantic Search, Neo4j, pgvector, Elasticsearch

Data scientist and machine learning expert with full-stack software engineering skillset and a proven track record of delivering innovative solutions across biotech, R&D, and tech industries. Skilled in leading teams, developing data pipelines, building machine learning models, designing experiments, and delivering full stack data-driven software websites and tools.

𝐌𝐢𝐜𝐫𝐨𝐬𝐨𝐟𝐭 𝐏𝐨𝐰𝐞𝐫 𝐁𝐈 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐞𝐫 // 𝐏𝐨𝐰𝐞𝐫 𝐁𝐈 𝐂𝐨𝐧𝐬𝐮𝐥𝐭𝐚𝐧𝐭 // 𝐄𝐱𝐞𝐜𝐮𝐭𝐢𝐯𝐞-𝐋𝐞𝐯𝐞𝐥 𝐃𝐚𝐬𝐡𝐛𝐨𝐚𝐫𝐝𝐬 I am Zeshan Ather, a Top 1% Expert-Vetted Professional on Upwork. Based in Silicon Valley, San Francisco, I bring over 11 years of experience in Data Analytics, Business Intelligence, and Data Science - including 9 years at Hewlett Packard Enterprise. With a Master’s in Computer Science (Data Science specialization, Software Development minor), I combine academic rigor with hands-on industry expertise to deliver enterprise-grade solutions. My career has been built on helping businesses unlock the full value of their data - whether through intuitive BI dashboards, scalable data pipelines, or AI/ML models that power predictive decision-making. 💡 What I Deliver: - Business Intelligence Dashboards: Power BI, Tableau, Qlik - executive dashboards, KPI tracking, drill-down analytics. - Data Engineering & Integration: ETL/ELT pipelines, SQL-based data modeling, Azure Synapse, Databricks, AWS Redshift, Snowflake. - Advanced Analytics & AI/ML: Forecasting, Churn Prediction, Recommendation Engines, NLP, Anomaly Detection, Predictive Maintenance. - Data Science Solutions: Machine Learning pipelines, Statistical Modeling, TensorFlow/Scikit-learn, Natural Language Processing, Experiment Design. - Cloud Data Platforms: Azure Data Factory, Azure Data Lake, Synapse Pipelines, AWS S3/Redshift, Snowflake, Delta Lake. - BI tools: Tableau/Tableau Server, Mode Analytics, Power BI, Oracle Hyperion, PowerPivot, PowerView, Looker, Mode, Sigma, Omni, Evidence - Database Platforms: SQL Server, MySQL, Amazon Redshift, Snowflake, Hadoop, Google Cloud, BigQuery, Postgres, Oracle, Supabase - SQL, Python, Hive, CMS integration, AWS - Agentic AI - Claude, Cursor 🔧 Technical Expertise: ✔️ BI Tools: Power BI, Tableau, QlikView, SSRS ✔️ Programming: Python, R, SQL, Scala, Spark, PSQL, DAX, MDX ✔️ Data Science: TensorFlow, PyTorch, Scikit-learn, Azure ML, NLP, Forecasting Models ✔️ Data Engineering: Azure Synapse, Data Factory, Databricks, Delta Lake, AWS Redshift, Snowflake ✔️ Databases: SQL Server, PostgreSQL, Vertica, MySQL ✔️ Modeling: Dimensional modeling, star/snowflake schemas, KPI frameworks ✔️ Security & Compliance: HIPAA, GDPR, PHI de-identification, RBAC, Row-Level Security 🌍 Trusted by Global Clients: - HPE (USA) - Data Analyst and Business Intelligence specialist - NHS (UK) – Healthcare dashboards & predictive models for patient outcomes. - Omni Tax Help (USA) – Sales analytics & forecasting models to improve client acquisition. - RealDefense (USA) – Product telemetry analytics + anomaly detection for cybersecurity products. - Inspire & Rozetree (USA) – Social media engagement analytics & automated campaign reporting. - MOTOR Magazine (USA) – Retail & operations analytics dashboards on AWS Redshift & Tableau. ✅ Why Work With Me: - 9+ years of end-to-end project delivery across BI, Data Science AI. - Strong communicator: making complex analytics clear to business leaders. - Proven success with 100% client satisfaction & 5★ reviews on Upwork. - Trusted by enterprises across healthcare, finance, marketing, retail, and cybersecurity. 👉 Whether you need BI dashboards, predictive ML models, or enterprise scale data pipelines, I deliver outcomes that move the needle for your business.