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Machine Learning (ML) Engineer- Core ML

Turnitin, LLC

Machine Learning (ML) Engineer- Core ML

Oakland, CA
Paid
  • Responsibilities

    Job Description

    Machine Learning is integral to the continued success of our company. We are significantly increasing our ML team over the next year in order to execute on an exciting and ambitious product roadmap. You will join a team of curious, helpful, and independent scientists and engineers, unified by a commitment to deliver cutting-edge, well-engineered ML systems.

    We are in a unique position to deliver powerful,  cutting edge Machine Learning to hundreds of thousands of instructors teaching millions of students around the world. Over 1B papers have been submitted to the Turnitin platform, and over 100M answers have been graded on Gradescope by Turnitin. Currently, ML powers in depth understanding of student writing, investigates authorship of student writing, groups handwritten student answers by content, and plays a crucial role in many back-end processes.

    Machine Learning Engineers focus on building resilient and scalable ML infrastructure including data ingestion and model training pipelines.  Additionally, ML Engineers train, deploy and update production ML models.

    This role will report into the Machine Intelligence team, and will support ML Engineering in the Authorship product.  The Authorship product extends Turnitin’s industry leading Academic Integrity suite by providing tools to help identify and prevent the rapidly growing problem of contract cheating in student and academic writing.  We do this by leveraging the latest advances in Data Science to bring forward predictions and insights on the writing style and consistency of every student, enabling educators and Academic Integrity Officers to make better decisions about the origin of a piece of writing with more context and clarity.

    We expect all Machine Learning Engineers to be strong software engineers with a passion for machine learning methods and applications. You will focus on building resilient and scalable ML infrastructure.  Additionally, you will help build turn-key model training pipelines and bring trained models to production, with some fluency in dataset construction and model training.

    Day-to-day, your responsibilities are to:

    • Write and review clean, efficient, and modular code, with automated tests and appropriate documentation.

    • Answer questions and make trainable datasets from raw data, using efficient SQL queries and scripting languages, visualizing when necessary.

    • Given trained model, deliver prediction-serving system with required scale, uptime, and monitoring.

    • Find the right model architecture and hyperparameters, debugging model along the way.

    • Stay up to date with technology, make good technological choices, and be able to explain them to the organization.

  • Qualifications

    Qualifications

    Required Qualifications

    • Experience with the above responsibilities.

    • Strong software engineering fundamentals (we use Python, Unix-based systems, git, and github for collaboration and review).

    • Essential dev-ops skills (we use on-prem hardware, AWS EC2/Batch/Lambda).

    • Essential machine learning development skills (we use sklearn, tensorflow, pytorch, jupyter).

    • At least 2 years of relevant development experience.

    • Bachelor’s Degree in Computer Science, Statistics, Applied Mathematics, or a related field.

    Desired Qualifications

    • Experience or interest in education and machine learning methods for education technology.

    • Interest in product thinking and empathy for the user.

    • Experience with cloud-based workflows.

    • Master’s Degree or PhD. in Computer Science, Statistics, Applied Mathematics, or a related field.

    • At least 2 years of Python development experience.

    • Previous experience in working with and developing machine learning infrastructure, models and pipelines.

    Additional Information

    Characteristics for Success:

    • Enthusiasm for solving challenging problems and not being thwarted by obstacles.

    • Ability to work independently with a consistently high output.

    • Excellent written and verbal communication skills.

    • Strong curiosity about the problems at hand, the field at large, and the best solutions.

    • Strong system level problem solving skills.