SEARCH

Machine Learning Engineer Resume Example

Resume Score: 80%

Love this resume?Build Your Own Now
MACHINE LEARNING ENGINEER
Skills
  • 5+ years of experience in machine learning, deep learning, data science, building ML Pipelines and data engineering
  • Frameworks: Hadoop, Apache Spark, Apache Pig, Apache Hive, HDFS
  • Programming Languages: Python, SQL, Java (limited)
  • Analytics: SparkML, numpy, pandas, scipy, scikit-learn, matplotlib


Education and Training
08/2014
Master of Science - Applied And Computational Mathematics
Rochester Institute of TechnologyRochester, NY
06/2012
Bachelor of Science - Information Science And Engineering
Visveswariah Technological University, NMITBangalore, India
08/2014
Master's ThesisRochester, NY

Classifying Mechanisms of Spiral Wave Breakup Underlying Cardiac Fibrillation Using Quantitative Metrics

Summary

As a results driven individual, I have successfully translated business requirements into models that were continuously improved and delivered tangible results. My core competencies lie in leading machine learning projects end-to-end with the ultimate goal of improving customer experience and driving business impact.

Experience
Machine Learning EngineerApple, Inc. | Cupertino, CA03/2018 - Current
  • Led the machine learning anti-spam efforts for iCloud mail and calendar. This included training and evaluating spam models, scheduling training pipelines, contributing to new feature enhancements in the models, and working with Privacy/Legal teams to ensure that all features and models were compliant with Apple's broader stance on user's data privacy and security
  • Deployed the first ever ML based anti-spam model for iCloud mail and calendar to production
  • Implemented the ability to run A/B experimentation in the calendar and mail systems. These A/B tests are now used to validate model performance prior to production
  • Automate the process of producing datasets for labeling and contributed to integration with labeling tools at Apple. Consolidated an effective approach for the evaluation of spam models in the absence of ground truth
  • Worked cross-functionally with various teams within ACS to develop reports and experimentation dashboards that can track the performance of production ML models
  • Maintenance and continuous improvement of production models post deployment
  • Responsible for driving efficiency to the core messaging engine for iCloud customers around their storage utilization by bringing machine learning and end-to-end optimization to the iCloud subscriptions funnel
  • Accountable for increasing storage tier conversion rates and improving the overall customer experience by reducing notifications and emails
  • Continuously driving the culture of data-driven decision making & optimization across the broader org through tech talks and representing the Apple Cloud ML team in various ML events across Apple
  • Instrumental in defining the trajectory of the only machine learning team within Apple Cloud Services (ACS) as one of the first few members. This includes defining the roadmap and the tech stack for the team
  • Hiring and mentoring team members
ICloud Big Data AnalystApple, Inc. | Cupertino, CA09/2016 - 02/2018
  • Designed and built an alerting model to detect anomalous data in the incoming data streams. The model consists of a forecasting component which utilizes regression with regularization to generate predicted values of key performance indicators. The model has high sensitivity and specificity and requires minimal human intervention leading to a more robust tracking system
  • Used a graph-based analysis to uncover large extensive networks of fraudulent iCloud users. This was used to expose vulnerabilities in the account creation process that was abused in the form of credit card fraud
  • Determined existing fraud trends in the creation of iCloud accounts and worked cross functionally with the Fraud team in adding new rules to suppress future creation of similar accounts
  • Improved iCloud customer experience by studying the effects of product changes, iOS launches and new features with special focus on churn analysis
  • Implemented a classification model to uncover the contributing factors towards iCloud churn
  • Involved in efforts to increase iCloud revenue by increasing iCloud user engagement and defining metrics to measure the same
  • Built forecasting models to predict adoption rates of iOS/macOS and device sales
Data AnalystApple, Inc. (Through Infosys, Ltd) | Cupertino, CA12/2014 - 08/2016
  • Led efforts in the quarterly budget reviews to report on stats across the iCloud org
  • Performed investigatory analyses to uncover reasons behind churn across various iCloud apps and services
  • Designed, implemented and automated a predictive model, which uses ARIMA components to forecast critical key performance indicators
  • Built an interactive D3 dashboard to reflect the results of the forecasting model
  • Performed ad hoc analyses to estimate the performance and behavior of product releases using SQL and Python
  • Automated data extrapolation and interpolation processes utilizing crontab script automation and python scientific libraries such as pandas, numpy, scipy and statsmodels
Build Your Own Now

DISCLAIMER

Resumes, and other information uploaded or provided by the user, are considered User Content governed by our Terms & Conditions. As such, it is not owned by us, and it is the user who retains ownership over such content.

Resume Overview

Companies Worked For:

  • Apple, Inc.
  • Apple, Inc. (Through Infosys, Ltd)

School Attended

  • Rochester Institute of Technology
  • Visveswariah Technological University, NMIT
  • Master's Thesis

Job Titles Held:

  • Machine Learning Engineer
  • ICloud Big Data Analyst
  • Data Analyst

Degrees

  • Master of Science - Applied And Computational Mathematics
    Bachelor of Science - Information Science And Engineering

Similar Resumes

View All
Machine-Learning-Engineer-resume-sample

Machine Learning Engineer

Kespry Inc.

Sunnyvale, California