Aditya Aayush

AI Researcher

Los Angeles, California, United States2 yrs 7 mos experience

Most Likely To SwitchAI ML Practitioner

Key Highlights

Expert in building high-performance machine learning systems.
Strong blend of academic training and industry experience.
Proficient in Natural Language Processing and Deep Learning.

Stackforce AI infers this person is a Machine Learning Engineer with expertise in AI-driven solutions for diverse applications.

Contact

Skills

Core Skills

Natural Language Processing (nlp)Deep LearningSpeech ProcessingFeature EngineeringLarge Language Models (llm)MlopsSqlApi TestingAgile MethodologiesCybersecurityWeb Development

Other Skills

LangGraphLarge Language Model Operations (LLMOps)Retrieval-Augmented Generation (RAG)PalantirDecision TreesTransformersAzure Kubernetes Service (AKS)Distributed TrainingMicrosoft Azure Machine LearningPySparkBERT (Language Model)Oracle DatabasePolicy ResearchMultithreadingMicrosoft Power Automate

About

I'm an AI Engineer focused on building practical, high-performance machine learning systems that solve real-world business challenges. My approach blends a solid understanding of mathematical foundations with hands-on experience, turning complex theory into solutions that work reliably in production. With a mix of rigorous academic training and industry experience, I'm committed to staying ahead in the constantly evolving AI and ML landscape. I'm always open to discussing new ideas, projects, or technologies. Feel free to reach out!

Experience

2 yrs 7 mos

Total Experience

10 mos

Average Tenure

1 yr 4 mos

Current Experience

Twg ai

2 roles

Senior AI Engineer

Promoted

Feb 2026 – Present · 4 mos · On-site

AI Engineer

Feb 2025 – Feb 2026 · 1 yr · On-site

LangGraphLarge Language Model Operations (LLMOps)Retrieval-Augmented Generation (RAG)PalantirDeep LearningNatural Language Processing (NLP)

Carnegie mellon university

Research Assistant

Nov 2024 – Jan 2025 · 2 mos · Pittsburgh, Pennsylvania, United States · Hybrid

Contributed to multivariate regression using Tessellated Linear Models and evaluated transformer-based, self-supervised, and multi-task learning approaches for age prediction from audio data.

Speech ProcessingFeature EngineeringDecision Trees

Nexteer automotive

Data Scientist Intern

May 2024 – Aug 2024 · 3 mos · Auburn Hills, Michigan, United States · On-site

Developed transformer-based models (BERT, RoBERTa) for automatic commodity classification and dimensional data extraction from unstructured text. Deployed them on Azure Kubernetes and built PySpark pipelines, processing 150K+ records in under 20 minutes.

Large Language Models (LLM)TransformersAzure Kubernetes Service (AKS)MLOpsDistributed TrainingMicrosoft Azure Machine Learning+2

Carnegie mellon university

2 roles

Teaching Assistant

Jan 2024 – Mar 2024 · 2 mos · Pittsburgh, Pennsylvania, United States · Hybrid

Course: Database Management

SQLOracle Database

Research Assistant

Nov 2023 – Mar 2024 · 4 mos · Pittsburgh, Pennsylvania, United States · Hybrid

Web DevelopmentPolicy Research

Cisco

2 roles

Software Engineer

Aug 2022 – Jul 2023 · 11 mos · Bengaluru, Karnataka, India · Hybrid

Built a real-time release tracking dashboard integrating data from Jira, ServiceNow, and qTest using Azure Service Bus and Python. Optimized performance with scalable message queuing and automated alerts, reducing release-reporting latency by 90%.

API TestingMultithreadingAgile MethodologiesMicrosoft Power AutomateAzure Service BusPowershell+1

Software Engineer Intern

Jan 2022 – Jun 2022 · 5 mos · Bengaluru, Karnataka, India · Remote

Automated configuration conflict detection for enterprise releases
Streamlined SharePoint updates, integrating requirements from various teams for automated insights.

Pega PRPCAgile MethodologiesPython (Programming Language)Powershell

Manipal institute of technology

Undergraduate Research Assistant

Oct 2021 – Aug 2022 · 10 mos · Manipal, Karnataka, India · Remote

Analyzed the performance of the Elliptic Curve Cryptography (ECC) algorithm against the RSA algorithm, which is used in IoT devices, by testing them on varying data sizes and tracking the time to encrypt and decrypt the data.

CybersecurityCryptographyInternet of Things (IoT)