Syed Ali
Fremont,CA
Summary
Interested in working with large scalable backend systems and data pipelines
Overview
6
6
years of professional experience
Work History
Software Engineer (Big Data Team)
23andme
11.2022 - Current
- Developed and updated algorithms to visualize genetic calling data, improving data analysis capabilities and assisting in future chip design.
- Designed and implemented backend services to ensure compliance with GDPR and CCPA requirements for stored genetic data.
- Led biweekly on-call rotations for compliance pipelines, ensuring data security and integrity.
- Collaborated with cross-functional teams to maintain high availability of genetic data.
- Worked on laboratory information management system software, ensuring data accuracy and reliability.
- Created and managed ETL pipelines for preprocessing genetic data, supporting machine learning model training.
Software Engineer (Underwriting Team)
Uplift
09.2021 - 11.2022
- Deployed scalable backend microservices using AWS Lambda functions with CloudFormation.
- Designed underwriting logic to optimize customer acceptance rates while minimizing default rates.
- Integrated machine learning models into the underwriting process, automating applicant default determinations.
- Designed and deployed an efficient pipeline for data scientists to deploy machine learning models rapidly.
Software Engineer (Search Team)
Flipp
05.2018 - 09.2019
- Revamped the search relevancy logic of the Flipp app to implement "premium boosting," resulting in a
- Improved the data curation pipeline, achieving consistent uptime and reducing downtime incidents.
- Developed new automated integration tests and optimized existing tests, resulting in more reliable alarming with zero false positives.
- Prototyped a successful item recommender system for A/B testing.
Education
Bachelor of Science - Computer Science
University of Toronto
05-2021
Skills
Languages/Frameworks
- Python
- Java
- Django
- FastAPI
- Node
- Expressjs
Software Tools
- Cloudformation
- Docker
- AWS
Testing/Automation & Continuous Integration
- CircleCi
- Jenkins
- Drone
- Pytest
Data Science/Machine Learning
- Apache Airflow
- Tensorflow
- Pytorch
- Sagemaker
Projects
Conditional Generative Adversarial Network
- Designed and developed a Conditional Generative Adversarial Network (GAN) to generate synthetic lung X-ray images. Model can be conditioned on healthy and diseased which will cause the GAN to output healthy and diseased lungs respectively
- Configured the model to conditionally generate images of either healthy or diseased lungs based on specified inputs.
- Created the model entirely from scratch, training it independently without the use of pre-trained weights.
- Produced synthetic X-ray data suitable for training additional machine learning models for tasks like disease classification.
- Implemented comprehensive, native data pre-processing to ensure the quality and consistency of generated images.
Timeline
Software Engineer (Big Data Team)
23andme
11.2022 - Current
Software Engineer (Underwriting Team)
Uplift
09.2021 - 11.2022
Software Engineer (Search Team)
Flipp
05.2018 - 09.2019
Bachelor of Science - Computer Science
University of Toronto
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