Soroosh Sohangir

I am an AI and machine learning leader with experience across generative AI, large language models, predictive analytics, advertising measurement, and computer vision. My work has centered on building real systems that move from research and prototyping into production environments with measurable business impact.

At Amazon and AWS, I led engineering and applied science teams delivering enterprise AI platforms, recommender systems, targeting products, and customer-facing machine learning solutions across multiple industries. That work included both internal platforms at Amazon scale and end-to-end applied ML engagements for enterprise customers.

Today, I am the Co-Founder & CEO of Regulate.care, where I lead product vision, engineering, data, and clinical collaboration for an AI-powered metabolic health platform spanning consumer apps, connected health data, and provider tools.

I hold a Ph.D. and M.S. in Computer Sciences and bring a leadership style grounded in technical depth, cross-functional execution, and strong mentorship.

1. 2025 — Present

   Co-Founder & CEO

   Regulate

   Lead product vision and business strategy for an AI-powered metabolic health platform, including iOS and Android apps, CGM integrations, and a provider portal. I manage engineering, data, and clinical teams to deliver secure, scalable, real-time personalized health insights while driving partnerships and growth.

   • Digital Health
   • Product Strategy
   • AI Platform
   • Mobile & Provider Tools
2. 2018 — 2025

   Senior Manager, Data Science (Applied Science)

   Amazon / AWS

   Directed machine learning and generative AI teams delivering production systems for Amazon and enterprise AWS customers. My work spanned enterprise assistants, retrieval-augmented generation, advertising targeting, recommender systems, NLP, forecasting, and computer vision, alongside mentoring teams and serving as an Amazon Bar Raiser for 250+ interviews.

   • Generative AI
   • LLMs & RAG
   • AWS
   • Recommenders
   • Computer Vision
3. 2017 — 2018

   Machine Learning Engineer

   Snap Inc.

   Developed advertising effectiveness models to measure and optimize Snapchat campaign performance, productionized large-scale data pipelines with Dataflow and Spark, and delivered analytics that informed campaign strategy and performance evaluation.

   • Ads Measurement
   • Spark
   • Dataflow
   • Analytics
4. 2017 — 2013

   Principal Data Scientist & Technical Lead

   SecureWorks

   Led teams of engineers and data scientists building fraud detection, attack prediction, event severity scoring, and churn prediction systems. The transaction modeling work alone drove savings exceeding $200 million by identifying risky high-volume transactions with high precision and strong AUC performance.

   • Fraud Detection
   • Security
   • Random Forest
   • Predictive Modeling

• Scope

  Production AI Systems Across Multiple Domains

  Built and led machine learning and AI systems spanning generative AI, large language models, recommender systems, predictive analytics, advertising measurement and targeting, computer vision, fraud detection, and digital health products.

• Impact

  Measured Outcomes at Enterprise Scale

  Delivered end-to-end machine learning programs that improved retention, revenue, operational efficiency, and model quality, including multimillion-dollar savings, multimillion-dollar revenue gains, major reductions in manual effort, and strong precision and recall in production environments.

• Leadership

  Cross-Functional Teams and Platform Leadership

  Led organizations that combined engineering, product, and applied science, coaching teams, setting technical strategy, and driving execution from early problem framing through deployment for both internal platforms and customer-facing products.

• Depth

  Research Depth Paired with Practical Execution

  My background combines a Ph.D. in machine learning with years of hands-on delivery in production systems, allowing me to connect research rigor with product strategy, scalable architecture, and real-world business outcomes.