Ritesh Pallod

Lead ML Engineer

Bengaluru, Karnataka, India8 yrs 5 mos experience

Most Likely To SwitchHighly Stable

Key Highlights

Expert in building scalable ML models and AI applications.
Proven track record in optimizing ML inference latencies and costs.
Strong background in developing end-to-end ML platforms.

Stackforce AI infers this person is a SaaS-focused Machine Learning Engineer with expertise in AI-driven applications.

Contact

Skills

Other Skills

PythonApache SparkDistributed SystemsData AnalysisData StructuresProgrammingBig DataExtract, Transform, Load (ETL)Machine LearningAlgorithmsC++CSQLLinuxScala

About

An engineer, experienced in building & deploying ML models at scale, creating AI driven applications end to end & platforms. My work is a mix of ml, platforms, backend, creating excel sheets, documents & JIRAs. I line my work tracks with overall business objectives (revenue, engagement) and try to tackle it with clinical precision while also donning different hats traditionally worn by Product, Program Managers. In my spare time, I read books, think things. What I may lack in years of experience, I gain in hard work, sincerity & passion for work. Here's the space I write about things & stuff - https://badpallod.substack.com/

Experience

Glance

4 roles

Senior Staff Machine Learning Engineer, AI

Promoted

Jan 2025 – Present · 1 yr 2 mos

Scaling AI Shopping for millions

Staff Machine Learning Engineer, AI

Jan 2024 – Dec 2024 · 11 mos

Building upon my work on Content Generation & still building react apps to facilitate automation of workflows. AIGC work is backed by heavy analytics & prediction models to do better at click through rate & timespent.
On the side working on Infra Cost Optimization initiatives that improve ML inference latencies & throughput & reducing our experiment costs

Machine Learning Engineer 3, ML Platforms & AI

Promoted

Jan 2021 – Dec 2023 · 2 yrs 11 mos

Part of the team building an ML Platform on top of GCP. Productionizing GANs, recommendation systems at scale, building ML based internal tools end to end & doing SQL in spare time. We got our serving infra to do 10 million predictions per second, 80k QPS within 250 p99 ms.
With advent of Gen AI, I transitioned into a role where I am working on identifying & implementing the AI breakthroughs happening in the world and converting them to new business usecases & internal productivity tools. Content Generation, Image Generation, "Docubot" (chatting with internal docs), lip syncing digital avatars - are some of the tech had a role to play in.
All these work pieces have resulted into a track - AIGC that is aimed at providing hyperpersonalized content generated via AI for the end user.

Machine Learning Engineer 2

Aug 2019 – Jan 2021 · 1 yr 5 mos

Working on the ML serving platform on Azure, creating feature pipelines, dashboarding to track metrics and building apps end to end (backend, frontend & ML), taking projects from POC to MVP by cracking every ML / product metric through thorough analysis and decisions.

Inmobi

Data Engineer 1

Jun 2018 – Jul 2019 · 1 yr 1 mo · Bangalore

Work includes contributing to user feature stores that house features for billions of users, building feature engineering pipelines for recommendation models, building user scoring model, managing and optimizing the DS Platform (Mesos + JupyterHub Setup) to cope up with the heavy resource consumption requirements from the Data Sciences & Product teams.

Bmc software

Intern

Jul 2017 – Jun 2018 · 11 mos · Pune, Maharashtra, India

Developed an ETL tool for fast retrieval of large data sets and data aggregation. This project was aimed at extracting millions of records from a data-warehouse, performing aggregation functions on it and providing a consolidated, processed result; exempting the client the overhead of processing individual data from the source.