Aaryan Garg

Lead ML Engineer

United States3 yrs 9 mos experience

Most Likely To Switch

Key Highlights

Achieved 95% accuracy in neural network model.
Developed LSTM model for genome classification.
Conducted research on ML inference at Apple.

Stackforce AI infers this person is a Machine Learning Engineer with a focus on Computer Vision and Data Science.

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Skills

Core Skills

Machine LearningSoftware DevelopmentTeachingData ScienceNatural Language ProcessingComputer Vision

Other Skills

3D RenderingAPI vulnerabilityARM Cortex-MAd fraud detectionAlgorithmsAmazon Web Services (AWS)Apache SparkC (Programming Language)C++CUDAComputer EngineeringComputer ScienceConvolutional Neural Networks (CNN)Data StructuresData compression

About

I aspire to pursue research in computer engineering and use my skills and interests and apply them to solve real world problems. I am extremely interested in machine learning, data science, software development and want to implement it in projects that have an impact on how people live.

Experience

Apple

2 roles

ML Software Engineer

Jun 2023 – Present · 2 yrs 9 mos · Cupertino, California, United States · On-site

Private Cloud Compute: ML Inference
Siri and Information Intelligence
Ad platforms research: ad fraud detection

Machine LearningML InferenceAd fraud detectionSoftware Development

Software Engineering Intern

May 2022 – Aug 2022 · 3 mos · Cupertino, California, United States · On-site

Studied natural language based features for detecting fraudulent ad interactions on Apple Ad Platforms.
Replicated user event patterns on a test device to explore bad behavior.
Discovered and brought to light, an API vulnerability which could be exploited to automate inorganic ad events

Natural Language ProcessingFraud detectionAPI vulnerabilitySoftware Development

Purdue vertically integrated projects (vip)

Neural Network Team Leader - Computer Vision for Forest Inventory Analysis

Aug 2021 – Apr 2022 · 8 mos · West Lafayette, Indiana, United States · On-site

Designed and trained the neural network (based on SegNet) for image segmentation.
Tuned the hyperparameters of the model and successfully implemented dataset augmentation.
Improved the accuracy of the model up to 95%

Neural NetworksImage SegmentationHyperparameter tuningMachine LearningComputer Vision

Purdue university elmore family school of electrical and computer engineering

Undergraduate Teaching Assistant

Jun 2021 – May 2023 · 1 yr 11 mos · West Lafayette, Indiana, United States · On-site

Teaching Assistant for:
Signals and Systems: ECE 30100 - Fall 2022, Spring 2023
Python and Data Science: ECE 20875 - Spring 2022
Transforming Ideas to Innovation I: ENGR 13100 - Fall 2021
Linear Circuits Lab: ECE 20007- Summer 2021, Fall 2021

Signals and SystemsPythonData ScienceTeaching

Purdue university

Undergraduate Student Researcher

May 2021 – Aug 2021 · 3 mos · West Lafayette, Indiana, United States · Remote

Worked on DNA Classifier under guidance of Professor Vaneet Aggarwal.
Developed LSTM model for determining population group of a person from genome sequence.
Implemented parser for .fastq genome data files.
Developed data compression and decompression algorithms for handling/storing genome data.
Achieved 65% accuracy for classifying people into 5 population classes.

LSTMData compressionGenome data handlingData ScienceMachine Learning