Sathvik is available for hire
Hire SathvikSathvik Chinta
Verified Expert in Engineering
Machine Learning Engineer and Software Developer
Location
Pittsburgh, PA, United States
Toptal Member Since
September 5, 2023
Sathvik是一名精通数据科学和软件工程的硕士研究生. 他专注于机器学习和人工智能，但在云系统、全栈和后端开发方面拥有丰富的经验. Sathvik可以使用Java、Python、c++、Kotlin和Go提供复杂的解决方案.
Portfolio
Coupang
Artificial Intelligence (AI), Machine Learning, Data Scientist, PyTorch...
Coupang
AWS IoT, Python 3, Amazon EC2, Amazon S3 (AWS S3), OneDrive, TensorFlow...
Coupang
SQL, Apache Hive, Zeppelin, Amazon EC2, Amazon S3 (AWS S3), PyTorch...
Experience
Availability
Part-time
Preferred Environment
Visual Studio Code (VS Code), Linux, Python 3, MacOS, Windows
The most amazing...
...我开发的是一个内部聊天机器人网络，使用自定义llm，可以相互沟通，回答用户的问题.
Work Experience
Data Scientist
2023 - 2023
Coupang
- 作为Rocket Growth团队的全职数据科学家，启动并领导了一个新项目，通过使用定制的大型语言模型(llm)将平台提升到一个新的水平。.
- Theorized, ideated, 并为法学硕士们部署了新的互动方式，以快速、安全地提供答案.
- 使用PyTorch创建模型来识别电子商务市场中的捆绑包.
- 积极使用Amazon S3、Amazon SageMaker、Amazon EC2等云技术.
- 使用hug Face和GitHub等开源存储库开发尖端模型.
- Suggested, prototyped, 并为团队记录了新技术的多个高价值用例.
- Used multiple Python libraries, including pandas, Polars, and NumPy.
技术:人工智能(AI)，机器学习，数据科学家，PyTorch, TensorFlow
Data Science Intern
2022 - 2022
Coupang
- 领导一个跨团队项目，使用计算机视觉算法识别电子商务市场中的不良行为者.
- 利用PyTorch和流行的机器学习模型(如YOLO)识别品牌.
- 使用Amazon EC2、Amazon S3和Microsoft OneDrive等云资源.
技术:AWS IoT, Python 3, Amazon EC2, Amazon S3 (AWS S3)， OneDrive, TensorFlow, TensorBoard
Data Science Intern
2021 - 2021
Coupang
- 与视觉智能团队合作完成一个项目，改进产品分类. 学会了如何从新兴的研究论文中阅读、语境化和实施主题.
- Used new frameworks and techniques, including Amazon EC2, Amazon S3, PyTorch, SQL, Hive, Zeppelin, Vim, and Linux command line.
- 处理具有数十亿行的大规模数据集，并使用SQL有效地组合表和创建训练, validation, and testing datasets.
- Implemented an end-to-end ML pipeline for our models in PyTorch, utilizing both text and image inputs to make classifications.
- 学习了如何为ML训练创建整洁、模块化和易于复制的代码. 该代码允许大量配置，并使其易于根据最终用户的愿望进行混合和匹配.
- Implemented groundbreaking techniques, such as automatic mixed precision, distributed data parallel, and decision-level fusion techniques.
- 在AWS上托管和训练一个模型，广泛使用Amazon EC2和Amazon S3. Collaborated with another intern to divide and conquer model production.
Technologies: SQL, Apache Hive, Zeppelin, Amazon EC2, Amazon S3 (AWS S3), PyTorch, Vim Text Editor, Linux
Software Engineering Intern
2021 - 2021
Amazon.com
- 与Amazon Lookout for Metrics团队合作，在很短的时间内了解了不同的AWS产品.
- 通过获取CSV和JSON输入文件并推断所有字段，在Lookout for Metrics中自动输入用户条目. 然后它会自动在网站上填写，并返回给用户确认.
- 使用Amazon的内部构建器工具创建API，以便与其服务交互. 在有多个成员的大型团队中工作，以达到最佳效果.
Technologies: CSV, JSON, AWS IoT, Kotlin
Software Engineering Intern
2020 - 2020
Coupang
- Built API tests in the Java source code using Spring and JUnit. 这些测试与我们的数据库交互，确保一切都正确无误，并按预期运行.
- Learned new frameworks and applications such as JUnit, Git, Spring, Google Puppeteer, and TensorFlow, 以及行业环境中的DevOps生命周期和敏捷开发方法.
- 利用Jenkins和其他持续集成工具为团队提供完整的DevOps管道.
- 创建了托管端到端测试的构建作业，并使用Groovy管道脚本自动触发和提供反馈.
- Used Puppeteer, automated web manipulation software, 为我们的服务和Jest框架创建端到端测试以进行测试和断言. All the tests were hosted on a custom Jenkins build.
- Suggested, learned, 并为ML目的创建了TensorFlow模型，将平台提升到一个新的水平. Used neural networks and boosted trees for different models.
- 用React创建工具来与多个api交互，并以干净和有组织的方式显示数据库中的信息.
Technologies: DevOps, Agile DevOps, JUnit, Java, Git, Spring, Puppeteer, Back-end, Full-stack, TensorBoard, TensorFlow, Python 3, Jenkins, React
Experience
Seattle PD Crime Analysis
其目的是创建一个数据科学项目来分析西雅图警察局(PD)的犯罪报告. My team cleaned, analyzed, and contextualized the data.
As part of the team, 我使用TensorFlow建立了机器学习模型，以高度准确地预测不同犯罪类别的犯罪数量. I also used dataset partitioning methods such as moving windows. 为了比较和对比不同的方法，为所有犯罪类别找到理想的模型, I utilized linear models, deep neural networks, convolutional neural networks, and recurrent neural networks with long short-term memory blocks.
该项目最终获得了最佳机器学习模型第三名.
As part of the team, 我使用TensorFlow建立了机器学习模型，以高度准确地预测不同犯罪类别的犯罪数量. I also used dataset partitioning methods such as moving windows. 为了比较和对比不同的方法，为所有犯罪类别找到理想的模型, I utilized linear models, deep neural networks, convolutional neural networks, and recurrent neural networks with long short-term memory blocks.
该项目最终获得了最佳机器学习模型第三名.
Mingle
http://github.com/NSC508/Hack-20/tree/masterA web app for connecting people during quarantine. 它将有相似兴趣和班级的人匹配起来，并支持班级学习小组和信息传递.
The front end was built with React and the back end with Python. 我从头开始开发后端，并在web应用程序中实现Firebase. 最终产品使用Google Authenticator进行登录，并使用Firestore作为数据库. I wrote Python code from scratch, allowing interaction with the database to add, query, and logically identify people with similar interests. For hosting my web server, 我使用Flask并创建了一个API作为后端Python代码和前端React代码之间的中介.
The front end was built with React and the back end with Python. 我从头开始开发后端，并在web应用程序中实现Firebase. 最终产品使用Google Authenticator进行登录，并使用Firestore作为数据库. I wrote Python code from scratch, allowing interaction with the database to add, query, and logically identify people with similar interests. For hosting my web server, 我使用Flask并创建了一个API作为后端Python代码和前端React代码之间的中介.
Skills
Languages
Python 3, Java, SQL, C++, Kotlin
Other
Data Structures, Machine Learning, Data Scientist, Software Development, Linear Algebra, Algorithms, Supercomputers, Artificial Intelligence (AI), CSV, Agile DevOps, Back-end, Full-stack
Libraries/APIs
TensorFlow, PyTorch, OneDrive, Puppeteer, React
Platforms
Visual Studio Code (VS Code)， Linux, MacOS, Windows, Docker, AWS IoT, Amazon EC2, Zeppelin, Firebase
Frameworks
JUnit, Spring, Flask
Tools
TensorBoard, Vim Text Editor, Git, Jenkins
Paradigms
DevOps
Storage
Amazon S3 (AWS S3), JSON, Apache Hive, Google Cloud
Education
2019 - 2023
Bachelor's Degree in Applied and Computational Mathematical Sciences
University of Washington - Seattle, WA, USA
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