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Machine Learning Engineer Resume

SUMMARY

  • Technical lead, Data Scientist, and Machine Learning (ML) engineer on multiple successful production ML/AI projects.
  • Core skills: software development (10 years), ML (5 years), Natural Language Processing/NLP (5 years), tech leading (3 years).
  • Published AI/ML researcher.
  • Technical skills include Python, R, SQL/NoSQL databases, distributed data stores (“Big Data”), and public cloud.
  • Flexible communicator (written and spoken) comfortable with technical and non - technical audiences.
  • Experience in finance, energy, retail, legal services, manufacturing, and healthcare industries.
  • Significant international and cross-cultural experience.

PROFESSIONAL EXPERIENCE

Confidential

Machine Learning Engineer

Responsibilities:

  • Build custom production ML systems for Confidential Cloud customers; advise customers (including C-level) on AI/ML strategy.
  • Built search tools to help US Patent and Trademark Office patent examiners ensure the validity of newly issued patents.
  • Built an ML system that makes daily interest rate estimates for $4T of financial assets for a major bank. Led a team of six. After the project, customer spend grew +489% over six months, and the customer is becoming a Confidential Cloud public reference.
  • Architected an ML-based pricing system for an e-commerce platform with $3B+ of annual purchases. Planned the $1M+ project to deploy the system. Expected additional profit from the system is $10M-$20M annually. Led one engineer.
  • Designed a Kubeflow/Kubernetes-based machine learning training and serving platform for a Fortune 100 manufacturer.
  • Built an NLP system to extract facts (e.g., chemicals, dosage) from unstructured paper pharmaceutical documents into structured (SQL) data for a healthcare company with $100B+ in annual revenue.
  • Wrote, with collaborators, two technical blog posts (12) on Confidential Cloud products. The posts have over 15,000 views.
  • Manage global AI/ML feature requests from Confidential Cloud customers, aid Product Managers with feature prioritization.
  • Trained over 1000 individuals (Googlers and public) in topics including NLP, Kubeflow, sequence models, and ML in production.
  • Co-wrote and maintain Confidential -wide legal guidance on safe and compliant use of public data.

Confidential

Senior Data Scientist

Responsibilities:

  • Built a (production) NLP pipeline that included structured prediction, unsupervised learning, and graph processing.
  • Conducted literature searches and implemented ML models from research articles, making changes to fit our use cases.
  • Designed and supervised a $250,000 data labeling project.
  • Won an internal technical award f or training the first deep learning model in my department.

Confidential

Senior Consultant

Responsibilities:

  • Wrote multiple sections of SunGard’s SEC Rule 613 bid and a whitepaper on our transaction processing system.
  • Developed a n ML model using SEC EDGAR financial filing data to predict future corporate bankruptcies.
  • Designed, built, and deployed a set of analytics and visualizations (Tableau/MySQL) for the CEO of an energy investment fund.
  • Received 2015 Confidential STAR award (awarded to 4 out of 200 consultants).

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