Anmol Suag

CTO

San Francisco, California, United States8 yrs 10 mos experience

Highly StableAI Enabled

Key Highlights

Led AI-first initiatives transforming workplace learning.
Developed patented personalization models for major clients.
Integrated scalable tools enhancing productivity and engagement.

Stackforce AI infers this person is a SaaS-focused AI and Machine Learning expert driving productivity solutions.

Contact

anmolsingh626@gmail.com LinkedIn

Skills

Core Skills

Ai AgentsProject ManagementGenerative AiLarge Language Models (llm)Predictive ModelingRecommender SystemsData ScienceSoftware Infrastructure

Other Skills

ActiveMQAlgorithmsAmazon Web Services (AWS)AnalyticsApache MesosApache SparkApache StormArtificial Intelligence (AI)Big DataCC (Programming Language)CSSCSS JavascriptCassandraData Mining

About

Engineering leader at Lyearn, building AI-first systems that redefine how people learn, grow, and get things done at work. I believe the future of software is invisible — powered by AI that understands your goals, nudges your progress, and adapts to how you think. My work sits at the intersection of ML, LLMs, and human productivity. https://reach.at/anmol

Experience

8 yrs 10 mos

Total Experience

1 yr 9 mos

Average Tenure

1 yr 9 mos

Current Experience

Lyearn

Head of Engineering

Sep 2024 – Present · 1 yr 9 mos

🚀 Leading the architecture and evolution of Lyearn — a unified Learning + Productivity platform built around the MGSA (Mindset, Goals, Skills, Activities) framework
🤖 Engineered Lyearn Coach, an AI copilot that delivers smart nudges, learning suggestions, and productivity insights right inside the user's workflow
📈 Built atomic skill-tracking, personalized learning paths, and OKR-linked performance systems to power upskilling and alignment across organizations
🎮 Integrated gamified experiences and real-time productivity scoring to boost engagement and drive continuous growth
🔌 Orchestrated scalable integrations with tools like Slack, Jira, Zoom, and HRIS — ensuring Lyearn becomes the invisible layer that drives learning at work

MCPAI AgentsKnowledge Graph-Based RecommendationRetrieval-Augmented Generation (RAG)Markov Decision ProcessesGenerative AI+2

Blueshift

3 roles

Lead Machine Learning Engineer

Promoted

Apr 2022 – Aug 2024 · 2 yrs 4 mos · San Francisco Bay Area · On-site

🧠 Led GenAI initiatives with OpenAI & Amazon Bedrock — built persona tagging, content generation, and rec engines showcased at AWS events
🛠️ Built full-stack LLM systems: prompt engineering, RAG pipelines, and fine-tuning for production use
🤝 Managed cross-functional squads, turning cutting-edge ML into high-impact features for enterprise clients

Generative AILarge Language Models (LLM)Predictive ModelingMachine Learning AlgorithmsAI Agents

Senior Machine Learning Engineer

Nov 2020 – Mar 2022 · 1 yr 4 mos · San Francisco Bay Area · On-site

🔍 Built advanced personalization models using Autoencoders, BERT embeddings, and LambdaMART — led to a patented reranking system
⚡ Delivered real-time recommendation systems powering Discovery, BBC, and LendingTree
📈 Balanced relevance, latency, and scale in live ML environments handling millions of users

Predictive ModelingMachine Learning

Machine Learning Engineer

Aug 2019 – Oct 2020 · 1 yr 2 mos · San Francisco Bay Area · On-site

📊 Built predictive models (XGBoost, H2O) and ALS-based recsys to forecast churn and drive conversions
🌍 Deployed ML systems serving personalized content across industries — media, fintech, e-commerce
🚀 Productionized pipelines end-to-end — from data engineering to model serving

Natural Language Processing (NLP)Machine Learning AlgorithmsRecommender Systems

Marin software

Data Science Engineer

May 2018 – Apr 2019 · 11 mos · San Francisco, California

📈 Designed ML models to predict ad performance and power intelligent bidding recommendations for digital marketers
🎯 Built a Multi-Armed Bandit–based Budget Allocation Engine for dynamic, data-driven budget distribution
⚙️ Used Scala for scalable ETL workflows and Python for algorithm prototyping and experimentation

Data ScienceGradient BoostingSupervised Learning

Sprinklr

Software Engineer

Jun 2015 – Jul 2016 · 1 yr 1 mo · Gurgaon

📊 Led development of the Benchmarking module to compare brand performance across social platforms using large-scale data processing
🧮 Built ranking algorithms and recommendation systems for the Social Business Index, improving brand scoring accuracy
🛠️ Gained hands-on experience with ElasticSearch, MongoDB, RESTful APIs, and AWS server infrastructure — from setup to scaling

Software InfrastructureEngineeringJavaREST APIsElasticSearch

Athabasca university

Mitacs Globalink Internship

May 2014 – Aug 2014 · 3 mos · Edmonton, Canada Area

🌎 Selected for the highly competitive Mitacs Globalink Research Internship to work on education tech in Canada
🛠️ Developed an Academic Analytics Tool to let educators query LMS data for insights using a portable UI
💻 Worked across JavaScript, PHP, and PostgreSQL to build core features and improve data accessibility in learning platforms

Indian institute of technology, bombay

Summer Internship

May 2013 – Aug 2013 · 3 mos · Mumbai Area, India

🧾 Built a web-based ticketing and customer support portal for the Aakash Tablet project
🧠 Mentored by Padma Shri Prof. D.B. Phatak at IIT Bombay, as part of a national education initiative
🇮🇳 Project acknowledged by the Ministry of Human Resource Development, Government of Indi

Indian institute of remote sensing , indian space research organization

Summer Internship

May 2012 – Jul 2012 · 2 mos · Dehra Dun Area, India

🛰️ Worked with raw satellite and sensor data to build a web app for data organization and analysis
🛠️ Developed custom tools to streamline geospatial data processing and visualization
🌐 Strengthened full-stack web development skills through hands-on research implementation