Amey Agrawal

AI Researcher

Atlanta, Georgia, United States10 yrs 3 mos experience

Most Likely To SwitchAI ML Practitioner

Key Highlights

Expert in machine learning and systems integration.
Developed high-performance log parsing algorithms.
Designed MLflow integration for data science platforms.

Stackforce AI infers this person is a Machine Learning Engineer with a focus on AI infrastructure and systems.

Contact

inspiria12@gmail.com LinkedIn

Skills

Core Skills

Machine LearningDeep LearningSystems Engineering

Other Skills

AI inference systemsAI infrastructureApache SparkBashCC++ElectronFuzzy LogicGPU time sharingGitGraphics DesignJavaJavaScriptKerasLLM inference systems

About

Systems of ML

Experience

10 yrs 3 mos

Total Experience

1 yr 9 mos

Average Tenure

3 yrs 9 mos

Current Experience

Microsoft

4 roles

Research Intern

May 2025 – Aug 2025 · 3 mos · Redmond, Washington, United States · On-site

Building AI inference systems

AI inference systemsMachine Learning

Research Intern

May 2024 – Aug 2024 · 3 mos · Redmond, Washington, United States · On-site

Building systems for long context LLM inference

LLM inference systemsMachine Learning

Research Intern

May 2023 – Aug 2023 · 3 mos · Bengaluru, Karnataka, India · On-site

Building systems for efficient LLM serving

LLM servingMachine Learning

Research Software Engineer 2

Jan 2021 – Aug 2022 · 1 yr 7 mos · Bangalore Urban, Karnataka, India

Worked on low-level systems to support efficient time sharing of GPUs in Singularity, Microsoft’s planet-scale AI infrastructure service.

GPU time sharingAI infrastructureSystems Engineering

Georgia institute of technology

Graduate Research Assistant

Aug 2022 – Present · 3 yrs 9 mos · Atlanta, Georgia, United States

Working on problems at the intersection of machine learning and systems.

Machine LearningDeep LearningPythonTensorflowSystems Engineering

Qubole

Member of the Technical Staff 2

Jul 2018 – Nov 2020 · 2 yrs 4 mos · Bengaluru, Karnataka, India

◦ Qubole MLflow: Designed and built modules end-to-end across the stack to integrate MLflow in Qubole ecosystem. Designed communication interfaces to glue the MLflow service with Qubole’s Jupyterlab platform.
◦ Managed RStudio Service: Integrated RStudio as a manged service within Qubole’s data
science platform. Contributed to S3FS improve cache performance and added support for persistent ACLs.
Received an early promotion as a result of this effort.
◦ Logan: Developed a distributed log parsing algorithm that provides 39x speed-up over the previous state-of-the-art. The system is used to perform real-time anomaly detection for all Apache Spark by processing over 250 million log lines every day. Received Spotlight award for this effort.
◦ Application Proxy: Redesigned the application proxy layer which reduced the page load times for Apache Spark UI by over 5x.

MLflowRStudiolog parsingApache SparkMachine Learning

Birla institute of technology and science, pilani

2 roles

Teaching Assistant | Machine Learning

Jan 2018 – May 2018 · 4 mos · Pilani

I served as a teaching assistant for 'BITS F464 Machine Learning' under the supervision of Prof. Tiwari. The responsibilities included developing course material in Python, tutoring, and grading tests.

Machine LearningPython

Teaching Assistant | Neural Networks & Fuzzy Logic

Aug 2017 – May 2018 · 9 mos · Pilani

I served as a teaching assistant for 'Neural Networks and Fuzzy Logic' course with Prof. Bhanot since fall 2017. I developed an Electron application for cross-platform evaluation and grading of Jupyter notebooks based assignment. I created Python assignments and tests along with conducting tutoring sections.

Neural NetworksFuzzy LogicElectronMachine Learning