Software Engineer, ML Infrastructure Platform

Nuro Inc.
Mountain View, CA, United States
24 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience required
1 year minimum
Working hours
Regular working hours

Tech stack

C++ (Programming Language) Python (Programming Language) Delivery Pipeline Kubernetes Machine Learning Operations Data Pipelines

Job description

Experteer Overview In this role you will support the ML infrastructure that powers the Nuro Driver, enabling scalable model training and deployment. You will work with cross-functional teams to keep training and release pipelines reliable and efficient. You’ll design and operate data pipelines, multi-cluster scheduling, and agentic-first ML workflows that are reproducible and extensible. This position offers the chance to improve observability, alerting, and incident response for critical autonomy development efforts. Compensation / Benefits * Contribute to training infrastructure across multi-generation accelerators and multi-cluster environments * Design and operate large-scale data pipelines (batch and streaming) and storage layouts * Develop agentic-first ML workflows from data to evaluation that are introspectable and reproducible * Own reliability for training and release pipelines, including instrumentation, alerting, and on-call practices Tasks * BS, MS, or PhD in CS, EE, or related field with 1+ years of experience * Willingness to deep-dive into implementation and raise engineering standards * Ownership mindset with drive toward operational maturity * Strong Python proficiency (and comfort with C++, Go or similar systems language) * Hands-on experience running production infrastructure on Kubernetes * Solid distributed-systems fundamentals and ability to reason about performance and reliability Key requirements * base pay (160,360-240,540) * annual performance bonus * equity * competitive benefits package

Requirements

aaal_ field, with 1+ years of experience * Willingness to deep-dive into implementation and raise engineering standards * Ownership mindset with drive toward operational maturity * Strong Python proficiency (and comfort with C++, Go or similar systems language) * Hands-on experience running production infrastructure on Kubernetes * Solid distributed-systems fundamentals and ability to reason about performance and reliability Key requirements * base pay (160,360-240,540) * annual performance bonus * equity * competitive benefits package

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Good distractions

Talks and stories from around this role — technically off-topic, practically not.

2:28 min

Understanding Kubernetes architecture and core cluster components

Marc Nimmerrichter ¡ World Congress 2022

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Applying software engineering environments and testing to data pipelines

Matthias Niehoff Matthias Niehoff ¡ World Congress 2024

1:51 min

Unifying software compliance into standard delivery pipelines

Marcus Ross Marcus Ross ¡ World Congress 2026 Europe

4:18 min

Prioritizing communication and structural awareness over strict tool mastery

Liam Hurrel +1 ¡ World Congress 2021

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Overview of Kubernetes operators and custom resource definitions

Philipp Krenn ¡ World Congress 2022

2:14 min

Exploring internal AI product initiatives and global engineering roles

Maria Apazoglou ¡ Coffee With Developers

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