Akaash Nidhiss Shanmugapandian — Lead ML Engineer

2+ yoe in engineering and product. A tech hobbyist who loves discussing startups, data science, and product. Working with smart people on 0 to 1 problem statements at work or on personal projects. DM me or contact me on akaashnidhiss@outlook.com📧 . . . Currently solving our 1 to 10 problems - here’s the 0 to 1 problems I’ve helped solve: 🌟Undergrad: ➡️ 𝘈 𝘉𝘭𝘰𝘨𝘨𝘪𝘯𝘨, 𝘔𝘦𝘥𝘪𝘶𝘮-𝘭𝘪𝘬𝘦 𝘢𝘱𝘱 - helping users find similar topics based on their reading history ➡️ 𝘚𝘮𝘢𝘳𝘵 𝘛𝘦𝘴𝘵𝘦𝘳 𝘈𝘱𝘱 𝘧𝘰𝘳 𝘴𝘤𝘩𝘰𝘰𝘭𝘴 - recommends questions tailored to student’s weaker concepts (as final Year B.Tech Project) 🌟ABB: ➡️ 𝘚𝘺𝘴𝘵𝘦𝘮 𝘧𝘰𝘳 𝘱𝘳𝘦𝘥𝘪𝘤𝘵𝘪𝘷𝘦 𝘮𝘢𝘪𝘯𝘵𝘦𝘯𝘢𝘯𝘤𝘦 - using IoT Sensor Data on Industrial Boilers to accurately predict downtimes (used LSTMs and Autoencoder Models) 🌟Kearney: ➡️ 𝘈𝘐 𝘘/𝘈 𝘣𝘰𝘵 - provides insightful, strategy-based answers (first of its kind in an enterprise at the time) ➡️ 𝘈𝘐 𝘈𝘶𝘵𝘰𝘮𝘢𝘵𝘪𝘰𝘯 𝘗𝘭𝘢𝘵𝘧𝘰𝘳𝘮 - automated AI algorithms to intelligently consolidate and label data, quickly gaining actionable insights (from MVP to Production) ➡️ The underlying AI algorithms that make the above possible. 𝐓𝐋𝐃𝐑: Working with great teams helps me build great products! I love connecting with Founders, Product Folk and those interested in AI/Business Strategy. also I don’t have a top mate link and don’t plan on having one If you’re a junior needing feedback (or) a senior willing to give feedback - feel free to message me here or via email :)

Stackforce AI infers this person is a SaaS and IoT-focused AI Engineer with strong product development skills.

Location: Gurugram, Haryana, India

Experience: 6 yrs 7 mos

Skills

Ai Engineering
Product Development
Data Analysis
Full-stack Development
Machine Learning
Data Science
Web Development
Software Development
Marketing Strategy
Communication

Career Highlights

Led development of enterprise AI products.
Built predictive maintenance systems using IoT data.
Converted internship into full-time role through innovation.

Work Experience

Kearney

Lead Applied AI Engineer, Core AI Innovation Team (2 yrs 8 mos)

Product Engineering Intern (3 mos)

ABB

Machine Learning and Data Science Intern (2 mos)

Nanua Global

Lead Backend Engineer (1 yr)

Entelyst

Marketing and Strategy Intern (1 mo)

Delhi Technological University (Formerly DCE)

Student (3 yrs 11 mos)

Education

Bachelor of Technology - BTech at Delhi Technological University (Formerly DCE)

High School Diploma at Delhi Public School - Doha, Qatar

Akaash Nidhiss Shanmugapandian

Lead ML Engineer

Gurugram, Haryana, India6 yrs 7 mos experience

AI ML PractitionerAI Enabled

Key Highlights

Led development of enterprise AI products.
Built predictive maintenance systems using IoT data.
Converted internship into full-time role through innovation.

Stackforce AI infers this person is a SaaS and IoT-focused AI Engineer with strong product development skills.

Contact

spakaashnidhiss@gmail.com LinkedIn

Skills

Core Skills

Ai EngineeringProduct DevelopmentData AnalysisFull-stack DevelopmentMachine LearningData ScienceWeb DevelopmentSoftware DevelopmentMarketing StrategyCommunication

Other Skills

AI productsAgile Product ManagementAlgorithmsBusiness StrategyC++DartData ModelingData StructuresDigital MarketingDigital MediaDigital StrategyEDAEmbedded JavaScript (EJS)Exploratory Data AnalysisExpress.js

About

Experience

Kearney

2 roles

Lead Applied AI Engineer, Core AI Innovation Team

Jul 2023 – Present · 2 yrs 8 mos

Led end-to-end development and product ownership of two enterprise AI products from concept to firm-wide rollout. Defined roadmap, drove engineering execution, working directly with Partners/CXOs on experiment results, product strategy, and roadmap decisions.
Scalable AI Backend Engineering & Pipeline Development
Built Product MVP, scaling backend architecture from 0-1 and 1-10.
Engineered a LangChain + Azure + Databricks modular backend, storage, and ETL pipeline system.
Designed an internal orchestration layer (LangGraph/ACA Jobs/Celery/Postgres) integrating procurement knowledge bases, business rules, and multi-model reasoning tuned for sourcing workflows.
Prototyped feasibility solutions for automated inventory review at a USD 200B+ retailer, adapting to evolving approval logic and schema changes to enable adaptive, repeatable inventory analytics.
Delivered Supplier Harmonization, Materials/SKU Harmonization, and Spend Categorization pipelines.
Impact: 8× throughput and ~90% faster delivery for 100+ consultants globally.
Enterprise & Client Impact
Spend Categorization engine deployed across 50+ global clients, analyzing billions in annual spend with hybrid multi model reasoning + rules-based accuracy controls.
Supplier Harmonization pipelines process 50K+ suppliers monthly across telecom, retail, logistics, and banking clients.
Full-Stack Platform Development
Delivered a supplier intelligence platform with ingestion, transformation, optimized SQL layers, and integrated spend repositories for high-performance analysis.
Built React dashboards enabling advanced filtering, data exports, natural-language search, and AI-assisted auto-correction.
Integrated AI-generated supplier profiles enriched with real-time news, SWOT metrics, and external market-intelligence APIs.

AI productsbackend architecturedata analysisSQLReactAI Engineering+1

Product Engineering Intern

Mar 2023 – Jun 2023 · 3 mos

Part of tiger team tasked with introducing Gen AI into digital assets
Developed a proof of concept within my first two weeks.
Focused on tech innovation & trying to find the balance between the tech’s feasibility (at the time) and delivering on high user expectations
Converted the internship to a full time opportunity after producing 3 locally hosted product MVPs

Gen AIproduct MVPstech innovationProduct DevelopmentAI Engineering

Abb

Machine Learning and Data Science Intern

Jun 2022 – Aug 2022 · 2 mos · Bengaluru, Karnataka, India

Built a system for predictive maintenance of an IoT powered industrial plant.
Was my first real hands on experience on messy data - responsibilities included:
cleaning data
EDA
data clustering using K-Means and DBscan
developing an LSTM Multivariate Feature Forecasting and LSTM AutoEncoder model
In order to achieve our prediction requirements.
What I was able to achieve?
Feature engineering and EDA reduced our IoT sensor groups from 52, to just 2.
Tuned our LSTM Feature Forecasting model to predict 100% of the breakdowns (with one false flag) in the industrial system.
Leveraged Python Libraries to intuitively visualize our data and accuracy, helping us show our algorithm methodology, grouping analysis and compare methods.

predictive maintenancedata cleaningEDALSTMMachine LearningData Science

Nanua global

Lead Backend Engineer

Jan 2021 – Jan 2022 · 1 yr · Delhi, India

Helped to design, develop, troubleshoot, deploy a website for Nanua Global, an Educational NGO by Dr. Rachna's Institute of spoken English & Literature.

website developmenttroubleshootingdeploymentWeb DevelopmentSoftware Development

Entelyst

Marketing and Strategy Intern

Dec 2020 – Jan 2021 · 1 mo · Doha, Qatar

Worked with the broader team and director to develop strategies for their online branding by 1) creating and delivering presentations for webinars to hire new talent and promote the brand, and 2) working with their software development team to promote new software in Qatar and the MENA region.
Achievements:
Led 5+ workshops and created marketing decks for Entelyst's cybersecurity products given to Company Leaders and other C-Level Executives by Entelyst,
Worked under Entelyst's SDE and Sales Outreach Team and learned how to develop client relations with MNCs involved in Banking, Government Services and Infrastructure, head quartered in Qatar.

online brandingpresentation creationclient relationsMarketing StrategyCommunication