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arjunaveerase

Arjun SE

@arjunaveerase

AI ML and Reinforcement Learning Engineer for 5G Wireless Communications

Indien
Englisch
Einige Informationen werden in englischer Sprache angezeigt.
Über mich
I am an AI/ML & Reinforcement Learning Engineer specializing in 5G, wireless communications, and signal processing. I bridge the gap between advanced deep learning frameworks and network architecture. My expertise includes building Hi-Fi communication projects using Python and designing custom RL environments based on Q-learning to optimize transceiver pipelines, rate-reduction, and bandwidth allocation. If you need mathematically rigorous, production-ready AI solutions or digital twins for wireless systems and predictive DSP, let's collaborate!... Mehr lesen

Kompetenzen

a
arjunaveerase
Arjun SE
offline • 
Durchschnittliche Antwortzeit: 1 Stunde

Meine Dienstleistungen

KI-Integrationen
I will build custom ai ml rl dl models in python

Portfolio

Arbeitserfahrung

Swiggy

Automation Solutions Developer

Swiggy • Vollzeit

Jan 2025 - Oct 20259 mos

Worked at Zepto Pvt. Ltd (Headquarters). Developed a high-scale Python automation suite called FastFwd: An Email automation platform, which is an in house, automation tool for large scale email automation for B2B logistics communications. Integrated Gmail API, SMTP, and Google Sheets to handle enterprise workflows across 1,350+ brands. Reduced manual processing efforts by 80% through robust programmatic execution and automated data validation pipelines, optimizing logistics data transactions valued over Rs. 27.5+ Crores.

Freelance_Web Designer

Simulation & Optimization Engineer

Freelance Web Designer • Vollzeit

Feb 2024 - Aug 20246 mos

Served as a Simulation Engineer onsite at ADE, DRDO, focusing on complex numerical modeling and parametric optimization. Leveraged high-fidelity simulation frameworks to design and validate high-frequency wave structures, achieving a -35 dB S11 optimization target. Conducted rigorous parametric sweeps and automated geometric data testing to optimize structural performance, successfully integrating the validated design model into high-profile autonomous systems.