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Developed APIs for digital marketing SaaS application. These APIs enabled data scientists and tech marketers to configure product offers, rewards and evaluate metrics for launch of digital campaigns. 

Deployed the application with multi-cloud and cloud-agnostic architecture. Engineered core parts of MLOps system including set up of databases, schemas for various cloud platforms. This infrastructure enabled offer generation through data pipelines and orchestration of workflows.

Led an initiative to enhance the efficiency of event hub ingestion and improve performance of Azure Cloud Functions.

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Developed a framework to integrate real-time application user data to a backend customer data platform (like mParticle) using webhooks to ensure efficient and accurate data flow.

Built AWS step functions and Terraform workflow infrastructure to ensure customers’ privacy and security compliance requirements are met in accordance with CCPA, SOC2 regulations.

Implemented novel ways to query customer datastore with millions of rows, columns using DynamoDB, AWS S3, and Athena.

Platform offering consumer intelligence solution. Its Customer Goal Management (CGM) platform enables clients to analyze customer data, behavior, and motivation and use reinforcement learning(RL) and target customers at the individual level by providing a personalized solution and not based on customer segments. The company serves industries such a

Platform offering consumer intelligence solution

Led a small team to develop platform log analysis tool for Intel ML Cloud. Used Java Spring as backend, and Swagger for API functions.

Provided tenant and module-level stats along with aggregation functions. This enabled KPIs and visual dashboards to help management understand application usage behaviors.

Developed extraction, transform, and load (ETL) data pipeline for operational insights. Gathered application runtime, memory and performance metrics for customer support and operation teams.

Designed a real-time anomaly detection engine to identify outliers in application behavior. Implemented Netflix’s RPCA algorithm to reduce manual effort in detecting usage patterns and uncovering potential app issues.

gov.il

Venrock

Glynn Capital

Herald Investment Management

Entertainment Media Ventures

DPH Ventures

Dassault Developpement

De Incubator

Draper Athena

Gen 1 Capital

POKU CAPITAL

B Capital Fund

Osmium Global

Intel Nervana (earlier Nervana Systems) provides end to end solutions to enterprises for deep learning based development. Products include Python based open source deep learning framework "Neo", a full-stack SaaS platform called Nervana Cloud that enables businesses to create their own custom deep learning models and Nervana Hardware which is an AS

Provides end to end infrastructure for deep learning development

Led automation projects to centralize the design data for 1 billion+ capacity chips. Built frontend, backend, and database components of this data pipeline for analytics and reporting. 

Provided Python REST APIs with CRUD operations to support circuit design teams. Enabled user and role-level data accessibility for efficient development process. 

Developed performance tools, database queries and stored procedures for insights to customer issues.

•	Performance research for automobile manufacturing and testing by developing vehicle simulators, and models.