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Machine Learning Engineer - Recommendations

Twitter
Full-time
On-site
Palo Alto, United States
$127,000 - $297,000 USD yearly

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!

  

Role: Machine Learning Engineer - Recommendations (All Levels)
Location: Palo Alto, New York City, London
Salary Range: $127,000 to $297,000 USD + Equity

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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. 


Your Role:

As a Machine Learning Engineer, you will be instrumental in crafting the most engaging experiences on X. Inspired by the success of Tesla's FSD v12, where an end-to-end AI system processes raw sensor input to make direct decisions, we are building end-to-end AI based recommendation algorithms. These algorithms aim to discover the most compelling content on X — including posts, promoted content, creators, and videos — based directly on users' activity on the platform. As a key driver of this effort, you will test state-of-the-art methodologies to significantly enhance users' experiences on the platform.

Your responsibilities will include:

  • Designing and architecting recommendation algorithms across various product surfaces in X (Timelines, Ads, Video, Search, Notifications)

  • Collaborating with cross-functional teams to integrate machine learning models into our platform

  • Iterating and improving the algorithm by gathering user feedback in real time through experimentation

  • Ensuring scalability and efficiency of machine learning systems

  • Mentoring junior engineers and contributing to the team's growth

  • Staying updated on Machine Learning and Deep Learning industry trends

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:

  • Master, Post-graduate or PhD in computer science, 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 recommender systems and/or deep learning applications (note - we are open to hiring for this role at all levels)

  • Good theoretical grounding in core machine learning concepts and techniques

  • Ability to perform comprehensive literature reviews and provide critical feedback on state-of-the-art solutions and how they may fit to different operating constraints

  • Experience with a number of ML techniques and frameworks, e.g. data discretization, normalization, sampling, linear regression, decision trees, SVMs, deep neural networks, bandits, reinforcement learning, etc.

  • Familiarity with one or more DL software frameworks such as Tensorflow, PyTorch.

At X, our small but fast-paced team values innovation, creativity, and a strong commitment to our mission. As a Machine Learning Engineer, 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.