Senior Machine Learning Engineer
2018 - PRESENTGPSE Consulting, LLC- Created a five-day machine learning engineering workshop to help companies bootstrap machine learning teams internally.
- Customized an online lab platform based on Jupyter to host workshops, including one-touch sign-in with YubiKeys.
- Provided consulting services to companies looking for machine learning expertise.
Technologies: Amazon Web Services (AWS), Scikit-learn, TensorFlow, PythonMachine Learning Engineer II
2015 - 2017Amazon Music (A2Z)- Developed a generative model for automated playlist creation.
- Designed a multi-modal approach to music classification to improve customer experience across several applications.
- Fixed genre misclassification issues for over 100,000 tracks.
- Acted as a machine learning consultant for several external teams.
Technologies: Amazon Web Services (AWS), Scikit-learn, TensorFlow, Spark, PythonSoftware Development Engineer II
2011 - 2015Amazon.com- Developed, and maintained a faceted search system with an attributed yearly sale of over $500 million.
- Developed, and deployed a new algorithm for faceted search across several categories and countries.
- Delivered over 10 tech talks on various topics such as AWS, machine learning, and crowdsourcing.
- Mentored five engineers, and interviewed over 130 candidates.
- Organized a Hackday for three consecutive years for an organization of over 300 engineers.
Technologies: Amazon Web Services (AWS), Python, JavaResearch Assistant
2009 - 2011Carnegie Mellon University- Maintained the Let's Go Bus information system.
- Transcribed over one million speech utterances with crowdsourcing.
- Organized monthly lunches on crowdsourcing for language technologies.
Technologies: Amazon Web Services (AWS), C++, Python
Gabriel Parent
Natural Language Processing (NLP) Developer in Seattle, United States
Member since May 13, 2019
Gabriel completed his master's before spending six years at Amazon working with the Search and Discovery team, and the Music organization. He has nine years of experience building distributed systems with AWS, including natural language processing, speech processing, recommendation systems, and deep learning. Gabriel is a team player who onboarded and mentored several new hires, and junior engineers at Amazon.
Gabriel is now available for hire
Portfolio
- GPSE Consulting, LLCAmazon Web Services (AWS), Scikit-learn, TensorFlow, Python
- Amazon Music (A2Z)Amazon Web Services (AWS), Scikit-learn, TensorFlow, Spark, Python
- Amazon.comAmazon Web Services (AWS), Python, Java
Experience
- Linux 16 years
- Python 12 years
- Natural Language Processing (NLP) 10 years
- Amazon Web Services (AWS) 10 years
- Machine Learning 8 years
- System Architecture 8 years
- Deep Learning 3 years
- Spark 3 years
Availability
Part-time
Preferred Environment
Amazon SageMaker, Spark, Jupyter, PyCharm, Git, Linux
The most amazing...
...algorithm I've developed helped millions of Amazon.com customers find the right products out of a catalog of billions of items.
Employment
Experience
- Fixing the Amazon.com Product Cataloghttps://patents.google.com/patent/US20150378975A1/en
One of my key contributions in my first role at Amazon was tackling the missing data problem: Not all attributes (e.g., hard drive interface, and capacity) are specified by merchants, although that information is often provided in the title or description.
I designed and coded several components of the larger pipeline my team was powering. More importantly, I developed a new algorithm for phrase extraction, and scaled it to handle thousands of categories, and billions of products across several marketplaces. EMR (Hadoop, Spark), S3, and several other AWS offerings were integral to the overall architecture, and are now essential elements of my design toolkit.
Knowing that my work had a significant positive impact on several downstream systems (recommendation, search, browse) was a great motivation, but the technical challenge was a driver too. Reprocessing a very large collection of text documents daily, and cost-effectively is not a trivial task. Applying machine-learning at that scale also comes with fun challenges.
Skills
Languages
Python, Java, Bash Script, SQL, JavaScript, C++, HTMLFrameworks
AWS EMR, Django, SparkLibraries/APIs
Scikit-learn, TensorFlow, Pandas, NumPyParadigms
Data Science, ScrumPlatforms
Android, Linux, Amazon Web Services (AWS), Amazon EC2, DockerStorage
Amazon S3 (AWS S3)Other
Machine Learning, Natural Language Processing (NLP), Data Mining, Information Extraction, System Architecture, Big Data, Deep Learning, Distributed Systems, Recommendation Systems, CythonTools
Amazon Elastic Container Service (Amazon ECS), Amazon SageMaker, Git, PyCharm, Jupyter
Education
- Master's Degree in Language Technologies2009 - 2011Carnegie Mellon University - Pittsburgh, Pennsylvania, USA
- Bachelor of Engineering Degree in Computer Engineering2005 - 2009École Polytechnique de Montréal - Montreal, Quebec, Canada
