Paarul Singh

Software Engineer

Bangalore Urban, Karnataka, India2 yrs 10 mos experience

Key Highlights

Proficient in MLOps and Microservices deployment.
Hands-on experience in application development and REST APIs.
Strong foundation in Deep Learning and Machine Learning techniques.

Stackforce AI infers this person is a skilled Software Engineer specializing in MLOps and Microservices within the tech industry.

Contact

paarulsingh511@gmail.com LinkedIn

Skills

Core Skills

MlopsMicroservices

Other Skills

AlgorithmsCC++CMakeConvolutional Neural Networks (CNN)Data ModelsData StructuresDeep LearningDockerDockerComposeFastAPIFastAPIsFlaskGitJIRA

About

I’m a computer science graduate with experience in software development. I’m passionate about learning new things and leveraging it to solve problems that can create a wider impact. I have hands-on experience in application development, RestAPIs,MLOps and Deep Learning. Please feel free to drop a hello or contact me at paarulsingh511@gmail.com if there is any opportunity contributing towards mutual growth.

Experience

2 yrs 10 mos

Total Experience

1 yr 5 mos

Average Tenure

1 yr 5 mos

Current Experience

Lenovo

SDE 2

Jan 2025 – Present · 1 yr 5 mos · Bengaluru, Karnataka, India · Hybrid

Intel corporation

2 roles

Software Engineer

Promoted

Aug 2023 – Jan 2025 · 1 yr 5 mos · Bengaluru, Karnataka, India · Hybrid

Software Engineer

Oct 2022 – Jul 2023 · 9 mos · Bengaluru, Karnataka, India · Hybrid

Actively contributed to the MLOps and Microservices team, acquiring in-depth knowledge of real-time deployment of machine learning models.
Applied proficiency in FastAPIs to write simple APIs and then develop automation scripts to test the complex ones in Pytest, as well as exploring additional functionalities.
Gained expertise in microservices and worked in its automation implementing processes and tools that streamline the development, deployment, scaling, monitoring, and management of microservices architectures.
Explored diverse facets of MLOps and related machine learning tools and techniques, actively engaging and conducting thorough analysis ensuring high-quality results.

MLOpsMicroservicesFastAPIsPytest