Prakhar Thakuria

Software Engineer

Hong Kong, Hong Kong6 yrs 10 mos experience

Most Likely To SwitchHighly Stable

Key Highlights

Proven expertise in Machine Learning and NLP.
Successful development of innovative data processing pipelines.
Strong foundation in Electrical and Electronics Engineering.

Stackforce AI infers this person is a Machine Learning and Software Development specialist with experience in SAAS and telecommunications.

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Skills

Core Skills

Natural Language Processing (nlp)Machine Learning

Other Skills

AlgorithmsAnalytical SkillsAngularJSAssembly LanguageBootstrapCC (Programming Language)C++Cascading Style Sheets (CSS)Computer VisionData AnalysisData ScienceDeep LearningDeep Reinforcement LearningElectronics

About

Wells Fargo || Adobe || IITM

Experience

6 yrs 10 mos

Total Experience

1 yr 10 mos

Average Tenure

5 yrs 10 mos

Current Experience

Daksh trading

Quantitative Software Developer

Sep 2023 – Present · 2 yrs 9 mos · Hong Kong, Hong Kong SAR

Wells fargo

4 roles

Senior Software Engineer

Promoted

Sep 2022 – Sep 2023 · 1 yr

Software Engineer

Dec 2021 – Aug 2023 · 1 yr 8 mos

Software Engineer Senior Analyst

Sep 2021 – Present · 4 yrs 9 mos

Program Associate

Aug 2020 – Present · 5 yrs 10 mos

Adobe

Tech Intern

May 2019 – Jul 2019 · 2 mos · Noida, Uttar Pradesh, India

Created an end-to-end pipeline to convert raw conversation to labelled data (Selected Prime Utterance to its Intent).
Achieved an accuracy bump of 9.47% on 10 across different cross-validation sets over models initially used by Adobe.
Build pipeline with concatenated models (adaptive and extractive) for summarization of conversation.
Developed a novel Extractive Summarization technique for summarizing customer support chat data.

Natural Language Processing (NLP)Machine LearningData Analysis

Bigcat wireless private limited

Tech Intern

May 2018 – Jul 2018 · 2 mos · Greater Chennai Area

Research and development intern worked on Full-Duplex problem with upcoming 5G Technology.
Modeled the Self Interference module for a realistic communication channel that used Machine Learning for noise cancellation. (Includes creating my own library to model OFDM of a signal).
Developed an application for simulation; Achieved more than 90 dB SIC and up to 97 dB SINR.

Machine LearningSignal Processing