Senior Software Engineer, ML Infra

Uber

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Hybrid

Quick summary

Work type: Hybrid
Location: Sunnyvale, CASan Francisco, CASeattle, WA
Posted: 75 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

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Similar $174k

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About Uber

Uber Technologies, Inc. is the world’s largest, San Francisco-based mobile technology platform facilitating on-demand ride-hailing, food delivery (Uber Eats), and freight transportation across approximately 70 countries.

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At a glance

TL;DR · Senior Software Engineer, ML Infra

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Senior Software Engineer – ML Infra will join the AI Infra - Training team to serve as a technical anchor for foundational systems. The role involves designing and building end-to-end systems for the ML training stack, specifically addressing scaling challenges for very large datasets and models. Key responsibilities include providing deep technical mentorship, creating tools and frameworks to increase engineering velocity, and using statistical analysis to diagnose performance regressions. The candidate must be proficient in programming languages such as Go, C/C++, Java, Python, or JavaScript. Required expertise includes state-of-the-art deep learning technologies, distributed training frameworks, LLMs, and GPU optimizations. This position focuses on solving complex infrastructure problems across global data centers and multiple cloud providers to ensure high-performance, fault-tolerant production environments.

What does a Software Engineer earn in California?

Median $214500 from 1193 postings across 76 companies.

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Skills

Distributed Training LLMs GPU Optimizations Go C++ Java Python JavaScript Distributed Computing Machine Learning Statistical Analysis ML Training Stack

What you'll do

Design and build end-to-end systems for the ML training stack to solve scaling challenges for large datasets and models.
Provide deep technical mentorship to ensure architecture and implementations are robust, extensible, and secure.
Use statistical analysis to diagnose performance regressions and optimize resource utilization across complex infrastructures.
Create tools and frameworks that increase the development velocity and quality for hundreds of internal engineering teams.
Lead engineers through code and design reviews while fostering a culture of continuous learning.
Work cross-functionally with Product, Data Science, and Operations to drive large-scale projects and align technical investments.

What we're looking for

6+ years of professional experience building scalable, fault-tolerant products or platforms.
Proficiency in one or more programming languages such as Go, C/C++, Java, Python, or JavaScript.
Proficiency in state-of-the-art deep learning technologies including distributed training frameworks, LLMs, and GPU optimizations.
Proven experience leading large-scale engineering projects from inception to global productionization.
Expertise in making complex engineering and business tradeoffs regarding "buy vs. build" or "incremental vs. rewrite" decisions.
Experience identifying architectural gaps and reducing technical debt across an organization.
Bachelor’s degree in Computer Science, Engineering, Mathematics, or equivalent practical experience.
Advanced degree (Master’s or PhD) in distributed computing, system performance, or machine learning (preferred).

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