Suresh A.

Key Skills

Software

No software listed

Top Subject Matter

AI industrial platform engineering (Asset AI, Maintenance AI, Operations AI, Digital FMEA) with digital twins and simulation

AI/ML asset health platform engineering with ML retraining governance

Edge IIoT data collection for analytics/AI-ready vibration and FFT feature generation

Top Data Types

3D Sensor

Image

Top Task Types

Text Generation

Function Calling

Data Collection

Classification

Freelancer Overview

Technical Architect for Field of Play (FOP) AI Platform — (Embedded/ Oil & Gas / Manufacturing). Brings 23+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Internal and Proprietary Tooling. Education includes Bachelor of Engineering, Computer Science, Vellore Engineering College (VIT Deemed University) (2000). AI-training focus includes data types such as ML, Computer Code, Programming, and 3D Sensor and labeling workflows including Text Generation, Function Calling, and Data Collection.

Labeling Experience

Technical Architect for Field of Play (FOP) AI Platform — Wipro (Oil & Gas / Manufacturing)

Text Generation

Architected and delivered a field-of-play AI platform on Microsoft Azure for Oil & Gas and Manufacturing clients, including multiple AI use cases such as Asset AI, Maintenance AI, Operations AI, and Digital FMEA. Designed the underlying data ingestion and event-driven alert pipeline using Azure Event Streams, KQL, and related Fabric/One Lake components to support AI model training and continuous learning workflows. Integrated NVIDIA Omniverse and NVIDIA Isaac Sim/Omniverse tooling with digital twin data for simulation-driven AI development. • Built Medallion Architecture on One Lake to structure data for AI/ML training. • Developed activator-based alert pipeline to trigger downstream AI processes. • Connected DTDL-based digital twin and simulation outputs to real-time ingestion. • Integrated enterprise systems (SAP BTP, IBM Maximo) for enrichment of AI-relevant data.

2025 - Present

Senior Architect for Asset Metrics Hub (AMH) & Asset Health Care (AHC) — Wipro

3D SensorFunction Calling

Designed an AI/ML-driven asset health platform that supports model retraining and governance over sensor-derived asset data used by plant engineers. Implemented an audit trail workflow enabling undo/redo and safeguarded training data access using security mechanisms including Binary Hash and X509-based controls. Established RBAC and SSO patterns so that model update and retraining workflows comply with enterprise governance for continuous AI operations. • Built 360-degree real-time dashboards with PI AF sensor integrations for training/monitoring data. • Designed ML model retraining pipeline and audit trail (undo/redo). • Applied Binary Hash, SSO, and X509 security across plant-level RBAC. • Supported ongoing AI operational workflows through secure data handling.

2022 - 2025

Sole Architect for HSDP MCS Control Portal — Wipro (Healthcare IoT)

Classification

Delivered an HSDP Healthcare IoT Cloud Foundry control API and gateway management portal designed to manage secure healthcare device data flows used for downstream AI analytics. Led development of gateway lifecycle management and remote firmware upgrade capabilities with multi-tier security controls (Binary Hash, OAuth2, X509). Provided structured access control and operational management functions that support consistent dataset generation and governance for AI/ML workflows. • Implemented MCS Control API and gateway management portal on Cloud Foundry. • Enabled secure gateway lifecycle management and remote firmware upgrade. • Delivered Linux diagnostics support for operational data quality. • Enforced multi-tier security to protect AI-relevant healthcare data flows.

2019 - 2020

Lead SECA Edge Computing Application — Ametek Instruments

3D SensorData Collection

Architected an IIoT edge computing application that captured offline and online vibration/FFT data to feed cloud streaming workflows used for analytics and AI development. Implemented CI/CD and security controls (Binary Hash, OAuth2, X509) to ensure the reliability and integrity of the collected instrument data used in downstream AI modeling. Enabled scalable cloud-connected instrument analytics by establishing Azure IoT Edge and Docker-based containerization patterns for repeatable data collection. • Set up Azure IoT Edge/Hub integration and MQTT-based telemetry for edge-to-cloud streaming. • Implemented offline data capture and online cloud streaming for rugged mining/manufacturing gateways. • Established containerized deployment pipeline to standardize data collection across sites. • Integrated FFT/vibration monitoring to generate AI-ready features from instrument signals.

2018 - 2018

Education

Work History