Machine Learning Platform Engineer

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!

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Who We Are:

At X, we’re pioneering the frontier of technology with our innovative Everything App. Our mission is to revolutionize how people connect, share ideas, and engage in meaningful conversations. We champion freedom of speech and strive to create a platform that embraces diverse perspectives. Our commitment is to foster open dialogue and empower individuals to express themselves freely.

We value:

• Writing code rather than documents

• Shipping products rather than talking about roadmaps

• Big features rather than changing button colors

If this sounds like you, let’s talk.

As an ML Platform Engineer, you will play a pivotal role in providing the most reliable and performant ML Platform experience on X. Your responsibilities will include:

• 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.

Who You Are:

We're looking for exceptional engineers who are passionate about our mission and have a strong desire to make a meaningful impact. The ideal candidate will have:

• 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

At X, our small but fast-paced team values innovation, creativity, and a strong commitment to our mission. You'll have the opportunity to make a significant impact on the future of X and our aspiration to build the Everything App. 

If you're an exceptional engineer who shares our passion for freedom of speech, we'd love to hear from you.