Platon Slynko
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Platon Slynko Email & Phone Number

GPU Performance Engineer at Silicon Data
Location: Ann Arbor, Michigan, United States 3 work roles 4 schools
1 work email found @kla-tencor.com LinkedIn matched
✓ Verified August 2026 4 data sources Profile completeness 86%

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Work email p****@kla-tencor.com
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Current company
Silicon Data
Role
GPU Performance Engineer
Location
Ann Arbor, Michigan, United States
Company size
7219 employees

Who is Platon Slynko? Overview

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Platon Slynko is listed as GPU Performance Engineer at Silicon Data, a with 7219 employees, based in Ann Arbor, Michigan, United States. AeroLeads shows a work email signal at kla-tencor.com and a matched LinkedIn profile for Platon Slynko.

Platon Slynko previously worked as AI Software Engineer at Kla and Data Engineering Intern at Publicis Groupe. Platon Slynko holds Master Of Artificial Intelligence, Artificial Intelligence, 3.8 from University Of Michigan.

Company email context

Email format at Silicon Data

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{first}.{last}@kla-tencor.com
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Profile bio

About Platon Slynko

I am an experienced AI software engineer with five years of expertise in building and optimizing deep learning platforms. My work spans data pipelines, including preprocessing, augmentation, and hyperparameter tuning for training, as well as designing efficient distributed inference workflows using multi-processing/threading/GPU. I’ve also explored advanced techniques like distributed K-fold, model recompilation, model intermediate node extraction, and layer freezing.Currently, I am pursuing a part-time master’s degree in AI to deepen my technical expertise and stay at the cutting edge of the field. My career has included contributions to Deep Learning projects and hackathons, where I’ve worked on solutions like an LLM-enabled legal document review platform and a real-time table-tennis game tracking with Deep Learning. Additionally, I have mentored interns, helping them grow and contribute to AI projects effectively.Currently, I am pursuing a part-time master’s degree in AI to deepen my technical expertise and stay at the cutting edge of the field. My career has included contributions to deep learning projects focused on advanced topics such as LLMs, RAGs, and CNNs/VAEs. I’ve also participated in hackathons, working on solutions like an LLM-enabled legal document review and real-time table-tennis game tracking using DL. Additionally, I have mentored interns, guiding them in projects ranging from exploration of potential AI technologies to developing AI distributed testing frameworks, helping them grow and effectively contribute to AI initiatives.I’m passionate about leveraging my expertise in AI and software engineering to tackle complex problems and drive meaningful impact. My focus is on optimizing efficiency and building robust, scalable solutions that push the boundaries of what technology can achieve.

Current workplace

Platon Slynko's current company

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Silicon Data
Silicon Data
GPU Performance Engineer
Ann Arbor, MI, US
Website
kla.com
Employees
7219
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3 roles

Platon Slynko work experience

A career timeline built from the work history available for this profile.

Ai Software Engineer

Current
Kla

Ann Arbor, Michigan, United States

𝗜𝗻𝘀𝗽𝗲𝗰𝘁𝗶𝗼𝗻 𝗿𝗲𝗽𝗿𝗼𝗱𝘂𝗰𝗶𝗯𝗶𝗹𝗶𝘁𝘆 𝗣𝗹𝗮𝘁𝗳𝗼𝗿𝗺 (𝘑𝘢𝘷𝘢, 𝘗𝘺𝘵𝘩𝘰𝘯, 𝘊++, 𝘛𝘦𝘯𝘴𝘰𝘳𝘍𝘭𝘰𝘸)Part of the founding team behind a GPU-powered HPC infrastructure for Deep Learning inference, adding capabilities to store/augment/debug/replay inspection jobs with data/parameters/results. • Configured environments for target hardware/software. • Built parallel data decryption pipelines and a multiprocessing inspection management server. • Enabled intermediate model node image retrieval and storage for debugging/training. • Developed Python interfaces for REST APIs and intermediate node datasets, including multi-inspection dataset matching.𝗗𝗲𝗲𝗽 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗧𝗿𝗮𝗶𝗻𝗶𝗻𝗴 𝗣𝗹𝗮𝘁𝗳𝗼𝗿𝗺 (𝘗𝘺𝘵𝘩𝘰𝘯, 𝘈𝘪𝘳𝘧𝘭𝘰𝘸, 𝘋𝘢𝘴𝘬, 𝘒𝘦𝘳𝘢𝘴/𝘛𝘦𝘯𝘴𝘰𝘳𝘍𝘭𝘰𝘸)Joined at the productization stage, driving the transition to a scalable, production-grade platform. Developed multi-stage deep learning and computer vision workflows, enabling advanced orchestration, efficient multiprocessing, and streamlined deployment. • Multi-GPU K-Fold Cross-Validation} (Python, Airflow, scikit-learn): Developed stratified K-fold with data splits on multi-format datasets. Leveraged Airflow for parallel GPU usage, improved training/inference efficiency and providing model generalization metrics. • Parallel Inference Job Platform (Python, Dask): Designed interleaved CPU/GPU pipelines using existing deep learning frameworks (TensorFlow, custom code) with a highly configurable architecture for maximum hardware utilization. • Integration Testing Framework (Python, Docker, CI/CD): Built an API framework for robust testing of models and platform workflows. Included results verification, flexible and scalable testing flows, and DL regression testing. Redesigned CI/CD deployment to streamline production and development container workflows.

Jun 2020 - Present

Data Engineering Intern

Publicis Groupe

Boston

Developed a distributed serverless ElasticSearch ETL data pipeline using orchestrated AWS Lambdas (orchestrator/indexing/worker fns) and AWS SQS.Auto-scalable to receiver throughput. Achieved an 80% operational costs reduction compared to Scala Spark.

Jun 2019 - Aug 2019
Team & coworkers

Colleagues at Silicon Data

Other employees you can reach at kla.com. View company contacts for 7219 employees →

NA Neal Ackerman Neal Ackerman Colleague at Silicon DataGreater Minneapolis-St. Paul Area, United States View → SW Shamim Wong Shamim Wong Colleague at Silicon DataSingapore View → PY Pin Yang Tan Pin Yang Tan Colleague at Silicon DataSingapore View → EF Edward Fu Edward Fu Colleague at Silicon DataHsinchu City, Taiwan, Province Of China View → TT Tuan Tran Tuan Tran Colleague at Silicon DataSan Jose, California, United States View → YC Yi Ching Chuah Yi Ching Chuah Colleague at Silicon DataHsinchu City, Taiwan, Province Of China View → GB Glenn Bayona Glenn Bayona Colleague at Silicon DataSingapore View → PL Pj Lpj Pj Lpj Colleague at Silicon DataTaoyuan City, Taiwan, Province Of China View → HW Hanbin Wang Hanbin Wang Colleague at Silicon DataShanghai, China View → JZ Jeffrey Zhang Jeffrey Zhang Colleague at Silicon DataHuangpu District, Shanghai, China View →
4 education records

Platon Slynko education

Master Of Artificial Intelligence, Artificial Intelligence, 3.8

University Of Michigan

Currently pursuing a part-time Masters program in Artificial Intelligence. Relevant coursework: Matrix Methods for Machine Learning.

Kla-Stanford Partnership, Cs229: Machine Learning, Artificial Intelligence, A

Stanford University

Attended "CS229: Machine Learning" class at Stanford with the help of KLA-Stanford partnership.

Bachelor Of Science (Bs), Electrical And Electronics Engineering

University Of Illinois At Urbana-Champaign

Relevant coursework: Algorithms and Data Structures, Data Science and Engineering, Artificial Intelligence, Data Mining, Fundamentals.

FAQ

Frequently asked questions about Platon Slynko

Quick answers generated from the profile data available on this page.

What company does Platon Slynko work for?

Platon Slynko works for Silicon Data.

What is Platon Slynko's role at Silicon Data?

Platon Slynko is listed as GPU Performance Engineer at Silicon Data.

What is Platon Slynko's email address?

AeroLeads has found 1 work email signal at @kla-tencor.com for Platon Slynko at Silicon Data.

Where is Platon Slynko based?

Platon Slynko is based in Ann Arbor, Michigan, United States while working with Silicon Data.

What companies has Platon Slynko worked for?

Platon Slynko has worked for Silicon Data, Kla, and Publicis Groupe.

Who are Platon Slynko's colleagues at Silicon Data?

Platon Slynko's colleagues at Silicon Data include Neal Ackerman, Shamim Wong, Pin Yang Tan, Edward Fu, and Tuan Tran.

How can I contact Platon Slynko?

You can use AeroLeads to view verified contact signals for Platon Slynko at Silicon Data, including work email, phone, and LinkedIn data when available.

What schools did Platon Slynko attend?

Platon Slynko holds Master Of Artificial Intelligence, Artificial Intelligence, 3.8 from University Of Michigan.

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