Sri Ramya Dumpala

Software Engineer

Bengaluru, Karnataka, India7 yrs 10 mos experience

Key Highlights

Expert in machine learning and software validation.
Proficient in embedded systems and automation development.
Hands-on experience with Intel platforms and Arduino.

Stackforce AI infers this person is a Machine Learning and Embedded Systems Engineer with strong software development skills.

Contact

Skills

Core Skills

Machine LearningSoftware DevelopmentEmbedded Systems

Other Skills

CC (Programming Language)C++CPU and Memory visualizationData Pre-processingEmbedded CLinuxModel EvaluationModel OptimizationModel TestingModel TrainingPythonPython (Programming Language)TKGTeamwork

About

working experience in machine learning, multi media, ADAS ,embedded system and software development ,end to end system & software validation and automation.

Experience

Broadcom

R&D software engineer 2

Nov 2023 – Present · 2 yrs 4 mos · India · On-site

CPU and Memory visualization, assignable Hardware. TKG

CPU and Memory visualizationassignable HardwareTKG

Vmware

Member Of Technical Staff 2

Apr 2021 – Nov 2023 · 2 yrs 7 mos · India

Sasken technologies limited

2 roles

Software Developer

Promoted

Nov 2018 – Mar 2021 · 2 yrs 4 mos · banglore

working experience in understanding of machine learning models and create the different use case scenarios and validated and verified on different Intel platforms like NUC, AI vision kit etc...
working experience in system and software validation and automation development using python

machine learning modelsuse case scenariossystem and software validationautomation developmentPythonMachine Learning+1

System software design and develop

Mar 2018 – Oct 2018 · 7 mos · banglore

Classify a given image of a handwritten digit into one of 10 classes representing integer values from 0 to 9 on Arduino Due board.
Programming Languages used: Python,C
Hardware Requirement: Arduino Due Board,SD Card, OV7670 camera sensor.
Roles & Responsibilities:
1. Data Pre-processing
2.Train a model
3. Test a model
4.Model Evaluation
5.Model Optimization.
Description:
Training a model using feedforward neural network in such a way that it looks at the image captured from the camera and predict what the digit is. The whole process should be done on Arduino Due board.