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far.ai

Senior Software Engineer, GPU Cluster Infrastructure

Join the far.ai research team to build and scale mission-critical, high-performance computing infrastructure for advanced AI models. This role is pivotal in managing our next generation of GPU compute clusters, ensuring optimal performance and availability for deep learning workloads. Key responsibilities include developing robust control planes using languages like Go, orchestrating resources via Kubernetes, and maintaining scalable distributed systems across diverse cloud environments. You will work closely with research scientists to translate complex computational needs into efficient, production-grade infrastructure solutions. Ideal candidates possess deep expertise in low-latency systems, cluster management, and a passion for advancing the frontier of AI computation.

far.ai Berkeley Office (Hybrid), United States

(تازہ ترین نوکریاں، سلیبس اور ٹیسٹ کی تیاری کی مکمل معلومات)

Preparing

1800

Question set

250

Duration

Permanent

Focus areas

GoKubernetesDistributed SystemsCloud InfrastructureGPU Computing

People Also Ask (FAQs)

What is the last date to apply for Senior Software Engineer, GPU Cluster Infrastructure?

The closing date is listed in the official advertisement — apply as early as possible.

How do I apply for Senior Software Engineer, GPU Cluster Infrastructure?

Use the official apply link on this page to submit your application. A step-by-step how-to-apply guide for this job is also linked below.

Is there negative marking in the far.ai test?

The marking rule is announced per test in the advertisement and roll-number-slip instructions. Many MCQ screening tests have no negative marking, but always verify it for your specific test.

What is the passing marks for this test?

The official passing marks are generally 50%, but merit is competitive — scoring above 75% is a safer target to secure an interview call.

How can I prepare for the Senior Software Engineer, GPU Cluster Infrastructure test?

Prepare with the free subject-wise MCQs, past papers and timed mock tests on PrepPro Academy — every question includes the answer with an explanation. Focus areas: Go, Kubernetes, Distributed Systems, Cloud Infrastructure, GPU Computing.

Quick start

Review the job summary, then jump into prep with the same flow used for exam starts.

Prepare for this test

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