Nirav Maheshwari

Software Engineer

Bengaluru, Karnataka, India5 yrs 4 mos experience

Highly Stable

Key Highlights

Proven expertise in Computer Vision and Deep Learning.
Successfully designed and implemented a classification model.
Strong foundation in Java and Machine Learning techniques.

Stackforce AI infers this person is a Machine Learning Engineer with a strong focus on Computer Vision and E-commerce applications.

Contact

Skills

Core Skills

JavaComputer VisionDeep Learning

Other Skills

TensorFlowdata generationcustom augmentationEfficientNetMachine LearningPython (Programming Language)C++competitive codingScikit-LearnkerasArtificial Neural NetworksReinforcement LearningPyTorchcOpenCV

About

I have an utmost level of enthusiasm while learning new skill set and powerful determination to do so.

Experience

5 yrs 4 mos

Total Experience

2 yrs 7 mos

Average Tenure

1 mo

Current Experience

Microsoft

Software engineer 2

Apr 2026 – Present · 1 mo

Arcesium

2 roles

Senior Software Engineer

Promoted

Jul 2023 – Apr 2026 · 2 yrs 9 mos

Software Engineer

Jul 2021 – Jul 2023 · 2 yrs

Java

Flipkart

2 roles

Data Science Intern

Apr 2020 – Jul 2020 · 3 mos · Bengaluru, Karnataka, India

Data science internship in the Catalog Data Science team at Flipkart where my task
was to design a model from scratch which will be used to classify top-wear apparel brands. Multi
task learning approach was used to do this with custom augmentation, data generation and
training. Tensorflow framework was used and EfficientNet was used as base model. Achieved
higher IoU score than the previous methods.

TensorFlowdata generationcustom augmentationEfficientNetComputer VisionDeep Learning

Data Science Intern

May 2019 – Jul 2019 · 2 mos · Bengaluru, Karnataka, India

Data science internship in the credit modelling team at Flipkart where my task was to
experiment and boost the performance of the SOTA LightGBM model by using Neural Network
on top of that and EDA. The model outperformed the LightGBM model which is SOTA for
structured data. Feature modelling, bayesian parameter optimization among other things were
used.