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Twitterposted 2 months ago
$127,000 - $297,000/Yr
Full-time • Entry Level
Seattle, WA
Professional, Scientific, and Technical Services
Resume Match Score

About the position

Are you prepared to join the X team and help build the ultimate real-time information-sharing app, revolutionizing how people connect? At X, we're on a mission to become the trusted global digital public square, committed to protecting freedom of speech and building the future unlimited interactivity. Our goal is to empower every user to freely create and share ideas, fostering open public discourse without barriers. Join us in shaping this thrilling journey where your contribution will be invaluable to our success! As an ML Platform Engineer, you will play a pivotal role in providing the most reliable and performant ML Platform experience on X.

Responsibilities

  • Build large-scale distributed machine learning systems which are scalable, performant, efficient and reliable.
  • Enabling teams to quickly test and iterate on their ML hypotheses via ML training capabilities, reliable GPU compute infrastructure and experimentation tools such as distributed deep learning libraries and Python notebooks.
  • Integrating X's GPU compute environment with large scale data and inference pipelines.
  • Work on ML frameworks such as Pytorch, Tensorflow, and/or feature management and vector databases such as Qdrant.
  • Learn new machine learning, deep learning, and/or natural language processing techniques for a variety of modeling and relevance problems involving users, their tweets, their interests, twitter ads, and relationships among entities.
  • Conduct online A/B testing, interpret and understand algorithm performance.
  • Collaborating with cross-functional teams to integrate machine learning models into our platform.
  • Mentoring junior engineers and contributing to the team's growth.
  • Participant in design and code reviews, team processes, and technical decisions.
  • Shape the future of development of Machine Learning Platform at X.

Requirements

  • Bachelor, Master, Post-graduate or PhD in computer science, computing engineering, machine learning, information retrieval, recommendation systems, natural language processing, statistics, math, engineering, operations research, or other quantitative discipline; or equivalent work experience.
  • 2+ years of industry experience working with high traffic or large ML production environments, distributed systems, backend infrastructure, recommender systems and/or deep learning applications.
  • 2+ years experience with ML problems and platform tools either through first-hand modeling or close collaboration with modeling engineers or data scientists.
  • Programming experience in Python, Rust or C / C++, Scala or Java.

Nice-to-haves

  • You are comfortable with Linux systems.
  • You have worked with Vector databases, GPU / CUDA programming.
  • You stay up-to-date on Machine Learning and Deep Learning industry trends.
  • You have low level understanding of compute systems such as distributed storage, NVIDIA drivers and CUDA toolkits.
  • You have worked with Slurm scheduler, Puppet or Ansible.

Benefits

  • Equity

Job Keywords

Hard Skills
  • Ansible
  • C
  • Java
  • Linux
  • Puppet
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