Adithya Hosapate

Software Engineer

Bengaluru, Karnataka, India5 yrs 9 mos experience

Most Likely To SwitchHighly Stable

Key Highlights

Expert in building scalable software solutions.
Strong foundation in deep learning and AI technologies.
Proficient in database management and real-time data processing.

Stackforce AI infers this person is a Backend-focused Software Engineer with expertise in AI and database technologies.

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Skills

Core Skills

Software DevelopmentNatural Language Processing (nlp)Database ManagementDeep Learning

Other Skills

MySQLElasticSearchPython (Programming Language)C++C (Programming Language)AlgorithmsData StructuresProgrammingMachine LearningSQLNoSQLMicroservices

About

IIT Hyderabad, class of 2020. Passionate about building scalable solutions for challenging problems. Also interested in deep learning and artificial intelligence.

Experience

5 yrs 9 mos

Total Experience

2 yrs 10 mos

Average Tenure

4 yrs 7 mos

Current Experience

Apple

Software Engineer

Oct 2021 – Present · 4 yrs 7 mos · Hyderabad, Telangana, India

Software Development

Aqr capital management

Analyst

Jul 2020 – Sep 2021 · 1 yr 2 mos · Bengaluru, Karnataka, India

Sms datatech corporation

Software Development Intern

May 2019 – Jul 2019 · 2 mos · Tokyo, Japan

PigAnalytics: Worked on the back-end of an Amazon seller analytics website. Gained experience
building a product entirely from scratch.
◦ Implemented the Trend microservice which extracts product trends in real-time from streamed
Twitter data using NLP. Served requests for keywords and product category trends.
∗ Also served requests for public opinion of products on Twitter, using sentiment analysis.
◦ Helped design the database layer, utilizing both RDMS(MySQL) and NoSQL(ElasticSearch) databases.
∗ Design could handle millions of Tweets and thousands of products/keyword trends per day.

Natural Language Processing (NLP)MySQLElasticSearchDatabase Management

Notionink design labs

Deep Learning Intern

Jun 2018 – Aug 2018 · 2 mos · Bengaluru Area, India

◦ Predictions In Blind Spots: Predicted movement of people across multiple surveillance cameras.
◦ Camera Net: Designed and implemented a neural network architecture to solve the above problem involving graph convolutions and LSTM networks.

Deep Learning

Commvault

Software Development Intern

Jul 2017 – Aug 2017 · 1 mo · Bengaluru Area, India

◦ Aggregating Data for Ransomware Detection: Utilized Logstash and Beats to process hundreds of thousands
of logs of packet data and Windows file data to detect ransomware attacks.
◦ Visual Programming: Utilized Blockly by Google to implement a prototype of visual programming to simplify
filtering of Logstash data.