Zach is available for hire
Hire ZachZach Nussbaum
Verified Expert in Engineering
Python Developer
New York City, United States
Toptal member since June 28, 2022
Bio
Zach is a machine learning engineer who started his career by working at Amazon as a software developer. He has experience building natural language processing models, leveraging unsupervised techniques, and using state-of-the-art large language models. Zach is excited about working on cutting-edge research and is currently building genomics-based models to improve molecular phenotype predictors.
Portfolio
Deep Genomics
Python, Google Cloud, TensorFlow, PyTorch
TopStonks
Python, PyTorch, Word2Vec, Scikit-learn, Amazon Web Services (AWS)...
Amazon.com
Python, PySpark, TensorFlow, Amazon Web Services (AWS)
Experience
- Python - 4 years
- TensorFlow - 3 years
- PyTorch - 3 years
- Amazon Web Services (AWS) - 3 years
- Google Cloud - 2 years
- PySpark - 2 years
- Flask - 2 years
- CircleCI - 1 year
Availability
Part-time
Preferred Environment
Visual Studio Code (VS Code), Python, TensorFlow, PyTorch
The most amazing...
...thing I've developed is a sentiment analysis model using transformers, weak supervision, and ensembling to classify r/WallStreetBets texts.
Work Experience
Machine Learning Engineer
2022 - PRESENT
Deep Genomics
- Led the machine learning engineering team in reducing repeated efforts and building tooling to improve the productivity of machine learning scientists.
- Utilized model distillation and TensorRT, a library that improves inference through reduced precision and layer fusing, to minimize the latency of sizeable deep learning models by approximately 16 times.
- Reimplemented DeepMind's Enformer paper in Keras on tensor processing units to share our available model architectures with the team. Explored the improvement of our existing baselines using new architectures.
- Built tooling to launch jobs on GCP Vertex AI, reducing the time to launch a job from two hours to 20 minutes.
Technologies: Python, Google Cloud, TensorFlow, PyTorch
Applied Machine Learning Engineer
2021 - 2022
TopStonks
- Fine-tuned a pre-trained transformer model using pseudo labeling and data augmentation to predict sentiment from Reddit's stock market data, beating the baseline transformer model by approximately 45%.
- Employed weak supervision and supervision to predict sentiment from Reddit's stock market data, improving the baseline transformer model by around 35%. The deployed model handles about 500,000 daily comments, which around 50,000 monthly users see.
- Developed and deployed a phrase-level trending topics model to identify what's interesting and unique in r/WallStreetBets using collocation detection to detect phrases and Word2Vec to cluster similar topics.
Technologies: Python, PyTorch, Word2Vec, Scikit-learn, Amazon Web Services (AWS), Transformer Models
Software Development Engineer
2020 - 2022
Amazon.com
- Maintained and improved evaluation pipelines for the Alexa Speech speaker ID model for 25+ million global consumers.
- Used PySpark to improve the runtime of big data processing by 25% and reduce job failures by 50%.
- Drove redesign and engineering for Alexa's speaker ID weekly evaluation pipeline, reducing manual work by 75%.
- Built the machine learning infrastructure for an ad ranking team using infrastructure as code with the AWS Cloud Development Kit.
- Optimized Amazon EMR clusters for the machine learning ad ranking team, reducing operational costs by 50% and leveraging AWS Lambda and Amazon EventBridge.
Technologies: Python, PySpark, TensorFlow, Amazon Web Services (AWS)
Experience
Sentiment Analysis Model for r/WallStreetBets
https://zanussbaum.substack.com/p/stonks-only-go-up-building-a-nlp?s=wDeveloped a machine learning model deployed on AWS that scores approximately 500,000 comments per day on Reddit's infamous r/WallStreetBets based on sentiment. This model was built using Snorkel and weak supervision.
Education
2016 - 2020
Bachelor's Degree in Computer Science
Davidson College - Davidson, NC, USA
Skills
Libraries/APIs
TensorFlow, PyTorch, PySpark, Scikit-learn
Tools
CircleCI
Languages
Python, TypeScript, Java
Platforms
Amazon Web Services (AWS)
Storage
Google Cloud
Frameworks
Django, Flask
Other
Hugging Face, Word2Vec, Machine Learning, Transformer Models
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