Siddhi Agrawal

Machine Learning Engineer

Bengaluru, Karnataka, India5 yrs 10 mos experience

Most Likely To SwitchHighly Stable

Key Highlights

Expert in building scalable data pipelines and ETL solutions.
Proficient in MLOps and optimizing machine learning workflows.
Strong background in AWS and performance benchmarking.

Stackforce AI infers this person is a SaaS-focused ML Engineer with expertise in data pipeline optimization and MLOps.

Contact

Skills

Core Skills

MlopsEtlData ProcessingData Transformation

Other Skills

AWSAWS GlueAlgorithm AnalysisAmazon Web Services (AWS)C (Programming Language)C++Cascading Style Sheets (CSS)Coding ExperienceCommunicationComputer Vision and Visual RecognitionData CollectionData Drift AnalysisData Driven ArchitectureData StructuresDatabase Management System (DBMS)

About

ML Engineer with expertise in building and optimizing scalable data pipelines, cloud-based ETL solutions, and machine learning workflows. My experience spans AWS, SageMaker, and performance benchmarking, where I focus on developing efficient ETL jobs, automating data transformations, and ensuring seamless model deployment. I have worked extensively on optimizing SageMaker inference response times, implementing Locust-based load testing, and streamlining ML operations through CI/CD automation using Jenkins. Passionate about solving complex data challenges, I thrive in designing robust architectures that enhance performance, scalability, and reliability in cloud environments. Always curious, always learning—excited about solving complex engineering challenges!

Experience

5 yrs 10 mos

Total Experience

2 yrs

Average Tenure

2 yrs 10 mos

Current Experience

Eagleview

2 roles

Machine Learning Engineer

Aug 2023 – Present · 2 yrs 10 mos

> Developing and optimizing models for aerial imagery, specifically focusing on line detection, roof, and facet segmentation.
> Successfully established MLOps processes for model training, versioning, and testing, ensuring seamless deployment and integration.
> Designed and implemented ETL pipelines using AWS Glue to transform and ingest large-scale data from S3 and PostgreSQL into structured datasets for analytics and machine learning.
> Designed and optimized data pipelines and also implemented an event-driven architecture leveraging Kafka, improving real-time data processing for model inference.
> Hands-on experience in managing complex machine learning projects from initiation to completion.
> Conducted thorough data drift analyses to identify potential biases in the datasets.
> Integrated Kafka into models to transition towards a data-driven architecture.
This holistic approach reflects my dedication to staying at the forefront of technological advancements in machine learning. Collectively , my skills in detecting lines, segmenting data, and overseeing entire machine learning projects showcase me as a capable machine learning engineer.

MLOpsETLAWSKafkaData Drift Analysis

Software Engineer Intern

Jan 2023 – Jul 2023 · 6 mos

The lnm institute of information technology

Teaching Assistant Computer Programming Course

Dec 2021 – Apr 2022 · 4 mos

Teaching and discussing the C++ topics , evaluating questions and solving doubts under the guidance of Prof Phillip Miller.

Aaveg- the lnmiit nukkad mandli

Core Member

Aug 2019 – Aug 2022 · 3 yrs

Performed 3+ street plays in a team of 20. Secured 1st place at Vivacity'19, the cultural fest of LNMIIT and Thomso Jaipur prelims'19 organized by IIT Roorkee. Performed at multiple flash mobs to aid in spreading awareness amongst the masses.