Amazon.com Services LLC
Direct employer career site

Member of Technical Staff - Infrastructure Engineer, Frontier AI & Robotics (FAR)

Pay
$150,000 per year
Location
San Francisco, CA
Listed
Today

About the role

Amazon's Frontier AI & Robotics (FAR) team is seeking a Member of Technical Staff, Infrastructure to build and scale the foundational systems that power our robotics research and development platform. In this role, you will design and operate the distributed infrastructure that enables our researchers and engineers to train foundation models, run large-scale experiments, and deploy intelligent robotic systems at Amazon scale.

Join the next revolution in robotics, where you'll work alongside world-renowned AI pioneers to push the boundaries of what's possible in robotic intelligence. As a Member of Technical Staff focused on Infrastructure, you'll build the critical platform layer that accelerates every aspect of FAR's research - from high-throughput data pipelines and experiment management systems to low-latency model serving and configuration delivery for robotic deployments.

This role is deeply technical and focuses on performance, scalability, and reliability at scale. You will design systems that support volumes of training data, operate with strict latency requirements, and provide the compute and data foundation that enables breakthrough research across FAR's robotics ecosystem.

Key job responsibilities

  • Design and build scalable compute and data infrastructure to support model training, inferencing, and eval for frontier AI/Robotics development
  • Lead large technical initiatives and shape the architecture of FAR's research platform infrastructure
  • Develop tooling and frameworks that accelerate research workflows, including dataset management, visualization, and quality assessment systems
  • Optimize query performance and data availability for experimentation and analytics workflows used by research teams
  • Improve the performance, efficiency, and reliability of FAR's core compute and storage infrastructure, ensuring systems remain fast and stable at scales
  • Build highly scalable experimentation and analytics infrastructure to support model evaluation, A/B testing, and feature performance
  • Collaborate directly with science and robotics teams to support research projects through both infrastructure development and hands-on technical contribution

Basic Qualifications

  • 5+ years of distributed systems experience
  • Bachelor's degree in Computer Science or a related field
  • Proficiency in Python and at least one systems or backend programming language (e.g., Go, Java, C++)
  • Experience with cloud infrastructure platforms (AWS, GCP, or Azure), including compute, storage, and networking services
  • Experience building or maintaining data pipelines, ETL systems, or ML training/serving infrastructure
  • Understanding of system reliability principles including monitoring, observability, fault tolerance, and on-call operational practices

Preferred Qualifications

  • Experience supporting AI/ML research workflows, including building and optimizing training stack, experiment tracking, dataset management, or model deployment infrastructure
  • Familiarity with robotics platforms, simulation environments, or real-time systems with strict latency requirements
  • Experience with large-scale data processing frameworks (e.g., Apache Spark, Flink, or Ray) and query optimization for analytics workloads
  • Demonstrated ability to lead large technical initiatives and influence architectural decisions across cross-functional teams
  • Experience building developer tooling, internal platforms, or self-service infrastructure systems that improve research or engineering productivity

Additional information

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.

Pay and benefits

Our compensation reflects the cost of labor across several U.S. geographic markets. The base pay for this position ranges from $150,000/year in our lowest geographic market up to $300,000/year in our highest geographic market. Pay is based on a number of factors, including market location, and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company.

Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits.

Read the original posting

From Amazon.com Services LLC's careers page, first listed on Rolev.ai on November 9, 2026. Rolev.ai is not the employer.

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Common questions

What is the salary for the Member of Technical Staff - Infrastructure Engineer, Frontier AI & Robotics (FAR) role at Amazon.com Services LLC?

The Member of Technical Staff - Infrastructure Engineer, Frontier AI & Robotics (FAR) posting at Amazon.com Services LLC states compensation of $150,000 per year. Final pay may depend on location, experience, and interview evaluation on Amazon.com Services LLC's official career site.

Where is the Member of Technical Staff - Infrastructure Engineer, Frontier AI & Robotics (FAR) job at Amazon.com Services LLC located?

This Member of Technical Staff - Infrastructure Engineer, Frontier AI & Robotics (FAR) position at Amazon.com Services LLC is located in San Francisco, CA. Always check Amazon.com Services LLC's application page for specific state eligibility or relocation policies.

How do I apply for the Member of Technical Staff - Infrastructure Engineer, Frontier AI & Robotics (FAR) position at Amazon.com Services LLC?

This listing links directly to Amazon.com Services LLC's application page. You can apply directly on Amazon.com Services LLC's site, or use Rolev.ai to check your resume fit, generate a zero-hallucination tailored resume and cover letter for this posting, and autofill the application form in 1 click with the Rolev.ai Chrome extension. You always review the form and press Submit yourself.