Rosi Reddy
Detroit
Summary
- With over 5 years of post-PhD experience in the field of ML/AI, I possess strong skills in model development and performance evaluation, and am proficient in Python and deep learning frameworks.
- Conducted research in both theoretical and practical machine learning, including Graph Neural Networks and Computer Vision and also have experience in Data Mining and Natural Language Processing.
- Have previous industry experience working at ByteDance on advertising monetization.
- Proficient in python, tensorflow, pytorch, data structure and algorithms.
- Actively seeking full-time positions in machine learning and data science.
- Professional with strong foundation in machine learning and data science, prepared to drive impactful results.
- Expertise in developing and deploying machine learning models, optimizing algorithms, and utilizing tools like Python, TensorFlow, and PyTorch. Known for excellent team collaboration and adaptability to evolving project needs.
- Proven ability to solve complex problems, deliver reliable solutions, and contribute effectively to team objectives.
Overview
7
7
years of professional experience
Work History
Machine Learning Engineer
TruEra
01.2023 - Current
- Pioneering research and productionization on actionable & interpretable strategies for LLM app evaluation at scale
- Successfully launched TruEra’s NLP diagnostics platform for explaining and debugging Transformer models, with support for Tensorflow, HuggingFace, and PyTorch
- Took neural network drift analysis and explainability projects from exploration to production
- Started and led TruEra’s first-ever mentorship and career development program
- Deployed machine learning models, ensuring seamless integration with existing systems.
- Automated data preprocessing pipelines using Python, streamlining data preparation for analysis.
- Developed GLANCE, a low-power computer vision sensor for object detection with ensemble cascading classifiers in a low-resolution and low-framerate environment
- Improved detection accuracy by 8% by designing a post-processing step involving dual IIR filters and stratification
Deep Learning Engineer
Kroger
06.2021 - 11.2022
- Oversaw end-to-end development and deployment of deep learning models for AI-assisted chip design
- Trained a transformer model to identify root crashes and errors from log files with 94% line classification accuracy
- Designed a recommendation system for clustering bugs and recommending improvements with historical data
- Co-authored 2 papers on gate sizing using Transformers with 98% accuracy and exponential runtime improvements against traditional EDA tools
- Conducted research on emerging deep learning trends, incorporating novel techniques into ongoing projects for continuous improvement of existing models.
- Contributed to the development of efficient data augmentation techniques that enhanced overall model performance.
- Developed an optimizer for tuning filtering parameters using analytical solvers on convex optimization problems that could be deployed and run offline
- Developed individualized learning plans for enhanced skill development.
Computer Vision Engineer
Vedanta Resources
09.2019 - 04.2021
- Developed GLANCE, a low-power computer vision sensor for object detection with ensemble cascading classifiers in a low-resolution and low-framerate environment
- Improved detection accuracy by 8% by designing a post-processing step involving dual IIR filters and stratification
- Developed an optimizer for tuning filtering parameters using analytical solvers on convex optimization problems that could be deployed and run offline
- Developed individualized learning plans for enhanced skill development.
- Fostered personal growth by providing guidance and support to mentees.
- Evaluated various deep learning frameworks and libraries for optimal implementation in computer vision projects, ensuring maximum compatibility and performance.
- Led software optimization efforts to reduce computational requirements, enabling deployment of computer vision applications on resource-constrained devices.
Machine Learning Researcher
Excitel Broadband
01.2018 - 08.2019
- I worked with a tear of data scientists to build and deploy production-ready applications.
- Developing a computer vision model to detect and classify objects in images.
- Building a computer vision mondel to track objects in videos.
- Developing and deploying computer vision software applications used to solve real-world problem's.
- Identifying and collecting relevant visual data from a variety of sources, and annotating the data to provide ground truth labels.
- Enhanced machine learning model performance by implementing advanced algorithms and feature engineering techniques.
- Reviewed existing codebases for any potential improvements and optimizations, contributing to a more efficient workflow for researchers.
- Led software optimization efforts to reduce computational requirements, enabling deployment of computer vision applications on resource-constrained devices.
Education
Master of Science - Computer And Information Sciences
Christian Brothers University
Memphis, TN12-2022
Bachelor of Science - Computer Science
KL
Guntur, India06-2018
Skills
- Tensorflow
- Algorithm and data structure
- Java
- Machine learning
- Model development
- Programming Python (numpy, pandas, scikit-learn), Deep Learning Frameworks (PyTorch, MXNet), R, C/C
- Big Data Accelerated Computing (CUDA), Cloud Computing (AWS, SageMaker), SQL
- DevOps Bash, Git, Docker, Open Source, Unit/Integration Testing, CI/CD
- Natural language processing
Websites
Dataprojects
- Neural Network Parser, Built an encoder-decoder model based on NMT (TensorFlow Neural Machine Translation) to train a neural network parser on the Penn TreeBank dataset
- PUBG Finish Placement Prediction, Kaggle competition, ranked 11% among all 1534 competitors, Predicted final placement from final in-game stats from over 65,000 games' worth of anonymized player data, Created feature engineering, built LightGBM model and used grid search CV algorithm to turn hyperparameters
Teachingandmentoringexperience
- Mentor of Practicum, Spring 2021, Fall 2019, Coached new graduate student instructors in Teaching Apprenticeship Program, provided written criticism of and consultation on classroom teaching practices
- Instructor and TA, 2018 - 2021, Taught: Methods and Techniques of Calculus, TA: Advanced Calculus and Fourier Analysis, Optimization and Introduction to Proofs
- Evening Tutoring Program, 2017 - 2018, Worked as tutor in the department's evening tutoring program, which serves undergraduate students taking calculus
Timeline
Machine Learning Engineer
TruEra
01.2023 - Current
Deep Learning Engineer
Kroger
06.2021 - 11.2022
Computer Vision Engineer
Vedanta Resources
09.2019 - 04.2021
Machine Learning Researcher
Excitel Broadband
01.2018 - 08.2019
Master of Science - Computer And Information Sciences
Christian Brothers University
Bachelor of Science - Computer Science
KL
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