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I’m an AI/ML Engineer based in Toronto with 4+ years of experience building full-stack, AI-driven applications using Python, React, and Node.js. I’ve worked on everything from scalable REST APIs and workflow automation to predictive analytics, NLP solutions, and lead scoring systems in Agile teams.…

Apurva Desai

AI Engineer, Full Stack Developer, Back-End Developer, +6

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I’m an AI/ML Engineer based in Toronto with 4+ years of experience building full-stack, AI-driven applications using Python, React, and Node.js. I’ve worked on everything from scalable REST APIs and workflow automation to predictive analytics, NLP solutions, and lead scoring systems in Agile teams.…

Available to hire

I’m an AI/ML Engineer based in Toronto with 4+ years of experience building full-stack, AI-driven applications using Python, React, and Node.js. I’ve worked on everything from scalable REST APIs and workflow automation to predictive analytics, NLP solutions, and lead scoring systems in Agile teams.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Language

English

Fluent

Hindi

Advanced

Work Experience

AI/ML Engineer at Salesforce

April 1, 2024 - Present

Developed AI-powered CRM workflow solutions using Python, React, Node.js, and REST APIs, improving customer query handling efficiency by 20%. Analyzed large-scale customer interaction datasets with NLP and ML to identify operational risk patterns and enhance support decision accuracy. Built and optimized machine learning models for lead scoring and anomaly detection, reducing manual review efforts by 35%. Implemented intelligent ticket prioritization and recommendation using Python, NLP, and classification models, reducing average support response time by 25% and improving issue routing efficiency. Partnered with operations, compliance, and support teams to improve AI workflow accuracy and strengthen enterprise data quality.

AI/ML Engineer at Salesforce Canada

April 1, 2024 - Present

Developed AI-powered CRM workflow solutions using Python, React, Node.js, and REST APIs, improving customer query handling efficiency by 20%. Analyzed large-scale customer interaction datasets using NLP and ML techniques to identify operational risk patterns and improve support decision accuracy. Built and optimized ML models for lead scoring, anomaly detection, and customer behavior analysis, reducing manual review efforts by 35%. Partnered with operations, compliance, and support teams to improve AI-generated workflow accuracy and strengthen data quality across enterprise systems. Implemented an intelligent ticket prioritization and recommendation engine using Python, NLP, and classification models, reducing average support response time by 25% and improving issue routing efficiency.

AI/ML Engineer at HubSpot

January 1, 2022 - July 31, 2023

Engineered an AI-powered prospecting agent using React, Node.js, LLMs, and NLP to automate company research, lead qualification, and personalized outreach. Developed predictive lead scoring models using CRM intelligence and behavioral analytics, improving lead targeting accuracy by 40%. Automated prospect enrichment workflows through HubSpot CRM APIs and backend automation pipelines, reducing manual research effort by 70%. Built NLP-based buying signal detection to identify high-intent prospects and improve outbound campaign efficiency. Created AI-generated outreach features using React and OpenAI APIs to generate personalized cold emails at scale, and collaborated with sales and marketing to build dashboards and workflow documentation for non-technical stakeholders.

AI/ML Engineer at HubSpot India

January 1, 2022 - July 1, 2023

Engineered an AI-powered Prospecting Agent using React, Node.js, LLMs, and NLP to automate company research, lead qualification, and personalized outreach. Developed predictive lead scoring models using CRM intelligence, Node.js services, and behavioral analytics, improving lead targeting accuracy by 40%. Automated prospect enrichment workflows through HubSpot CRM APIs and backend automation pipelines, reducing manual research effort by 70%. Built NLP-based buying signal detection systems with Python and Node.js to identify high-intent prospects and improve outbound campaign efficiency. Designed AI-generated outreach features using React, OpenAI APIs, and scalable backend services to create personalized cold emails at scale. Collaborated with sales and marketing teams to build dashboards, presentations, and workflow documentation for non-technical stakeholders.