X AI

2 days ago

ML Infrastructure Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

Build and optimize the high-performance ML platform powering recommendations on X. Design and scale GPU compute infrastructure, training frameworks, and experimentation tools for fast iteration. Develop data pipelines and productionize ML models through seamless integration across the stack. Own reliability, scalability, and efficiency for large-scale machine learning systems, while mentoring junior engineers and solving complex problems end to end.

Location: Palo Alto

Workplace: Onsite

Employment Type: Full time

Job Function: DevOps, Cloud & Infrastructure

Key Responsibilities

•Design, build, and scale GPU compute infrastructure, training frameworks, and experimentation tools for rapid ML iteration.
•Develop data pipelines and integrate large-scale data across training and inference systems.
•Collaborate with ML teams to productionize models and ensure seamless integration across the stack.
•Ensure scalability, reliability, and efficiency of large-scale machine learning systems.
•Work across the full stack to solve complex problems independently while mentoring junior engineers.

Pay and Benefits

Salary: USD 180,000 - 440,000 annually

Equity and Bonus:Equity

Perks:EquityHealth InsuranceVisionDental401k

Key Requirements

•Bachelor, Master, Post-graduate, or PhD in computer science, machine learning, or a quantitative discipline (or equivalent work experience).
•2+ years of industry experience in high-traffic or large-scale production environments, distributed systems, GPU infrastructure, and/or deep learning applications.
•2+ years experience with ML platforms, training infrastructure, or close collaboration with modeling engineers and data scientists.
•Strong proficiency with Python and experience with compiled languages such as C++ or Rust.
•2+ years experience with ML platforms, training infrastructure, or close collaboration with modeling engineers and data scientists.

Experience:2+ yearsMachine learningDeep learningDistributed systemsGPU infrastructureProduction systems

Education:

Skills:CommunicationMentoringPrioritizationCuriosity

Languages:English

Tech Stack:PythonC++RustJAXPyTorchLinuxCUDANVIDIASlurmPuppetAnsible

Company Brief

X AI

Develops advanced artificial intelligence models and research aimed at building safe, general AI and understanding the fundamental nature of the universe. Focuses on large-scale AI systems, research publications, and building foundational AI capabilities.

Industry: AI & Machine Learning

Company Size: Medium (51 to 250 employees)

Growth: Early Stage Startup

Headquarters: San Francisco, United States

Founded: 2023

Website

Loading job details...

Preparing the role view and application actions.

X AI

2 days ago

ML Infrastructure Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

Location: Palo Alto

Workplace: Onsite

Employment Type: Full time

Job Function: DevOps, Cloud & Infrastructure

Key Responsibilities

•Design, build, and scale GPU compute infrastructure, training frameworks, and experimentation tools for rapid ML iteration.
•Develop data pipelines and integrate large-scale data across training and inference systems.
•Collaborate with ML teams to productionize models and ensure seamless integration across the stack.
•Ensure scalability, reliability, and efficiency of large-scale machine learning systems.
•Work across the full stack to solve complex problems independently while mentoring junior engineers.

Pay and Benefits

Salary: USD 180,000 - 440,000 annually

Equity and Bonus:Equity

Perks:EquityHealth InsuranceVisionDental401k

Key Requirements

•Bachelor, Master, Post-graduate, or PhD in computer science, machine learning, or a quantitative discipline (or equivalent work experience).
•2+ years of industry experience in high-traffic or large-scale production environments, distributed systems, GPU infrastructure, and/or deep learning applications.
•2+ years experience with ML platforms, training infrastructure, or close collaboration with modeling engineers and data scientists.
•Strong proficiency with Python and experience with compiled languages such as C++ or Rust.
•2+ years experience with ML platforms, training infrastructure, or close collaboration with modeling engineers and data scientists.

Experience:2+ yearsMachine learningDeep learningDistributed systemsGPU infrastructureProduction systems

Education:

Skills:CommunicationMentoringPrioritizationCuriosity

Languages:English

Tech Stack:PythonC++RustJAXPyTorchLinuxCUDANVIDIASlurmPuppetAnsible

Company Brief

X AI

Industry: AI & Machine Learning

Company Size: Medium (51 to 250 employees)

Growth: Early Stage Startup

Headquarters: San Francisco, United States

Founded: 2023

Website