Sr ML Engineer

$149,000 - $199,800/Yr

Unclassified - Los Angeles, CA

posted 3 months ago

Full-time - Mid Level
Los Angeles, CA

About the position

At Disney Entertainment & ESPN Technology, we are dedicated to reimagining the way audiences experience our beloved stories through innovative technology. As a Senior Machine Learning Engineer, you will play a pivotal role in developing, implementing, and maintaining Hulu's recommendation and personalization algorithms. This position requires collaboration with various teams, including Engineering, Product, and Data, to apply advanced machine learning techniques that align with our strategic personalization goals. You will be at the forefront of exploring cutting-edge methods for recommendations, constantly optimizing our processes to enhance user experience and business outcomes. Your responsibilities will include utilizing state-of-the-art machine learning methods to develop algorithms for personalization and recommendations, ensuring they are integrated into a large-scale real-time recommendation pipeline. You will also maintain algorithms deployed in production and serve as the primary point of contact for explaining methodologies to both technical and non-technical teams. Additionally, you will be responsible for developing and maintaining ETL pipelines, deploying scalable streaming and batch data pipelines to support petabyte-scale datasets, and establishing best practices for algorithm development, testing, and deployment. Collaboration is key in this role, as you will work closely with product and business stakeholders to identify and define new personalization opportunities. You will also engage with data teams to enhance our data collection, experimentation, and analysis processes. This position offers a unique opportunity to reshape the future of Hulu's recommendation system by challenging the status quo and making strategic technological decisions that drive our business forward.

Responsibilities

  • Utilize cutting edge machine learning methods to develop algorithms for personalization, recommendation, and other predictive systems.
  • Maintain algorithms deployed to production and explain methodologies to technical and non-technical teams.
  • Develop and maintain ETL pipelines using orchestration tools.
  • Deploy scalable streaming and batch data pipelines to support petabyte scale datasets.
  • Establish and maintain algorithm development, testing, and deployment standards.
  • Identify and define new personalization opportunities with product teams.
  • Work with data teams to improve data collection, experimentation, and analysis.

Requirements

  • Bachelor's degree in Computer Science, Information Systems, Software, Electrical or Electronics Engineering, or comparable field of study, and/or equivalent work experience.
  • 5+ years of experience in developing highly scalable machine learning products.
  • 5+ years writing production-level, scalable Python codes.
  • In-depth understanding of deep learning technology in recommendation system or NLP fields.
  • Proficiency in at least one of the following deep learning frameworks: TensorFlow, PyTorch.
  • Experience deploying and maintaining pipelines (AWS, Docker, Airflow) and engineering big-data solutions using technologies like Databricks, S3, and Spark.
  • Experience building and deploying full stack ML pipelines: data extraction, data mining, model training, feature development, testing, and deployment.
  • Ability to articulate the usage and behavior of models and algorithms to both technical and non-technical audiences.

Nice-to-haves

  • MS or PhD in statistics, math, computer science, or related quantitative field.
  • Familiarity with Java and/or Scala programming languages.
  • Production experience with developing content recommendation algorithms at scale.
  • Familiarity with metadata management, data lineage, and principles of data governance.
  • Experience building streaming data pipelines using Kafka, Spark, or Flink.

Benefits

  • Medical benefits
  • Financial benefits
  • Bonus and/or long-term incentive units may be provided as part of the compensation package.
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