Staff Software Engineer Jobs in San Francisco (No ghost jobs, direct from employers)
- $254K median pay
- 10% remote
Staff software engineer jobs in San Francisco and the surrounding area, including hybrid roles based there, checked every hour. Pay where listed, posting age, company reviews and a ghost-job check on every posting.
501 jobs found
- 1 day agoLow ghost riskUberRemoteSan Francisco, CA$232K - 258KLead
- 1 day agoLow ghost riskCollective Hub Inc.HybridSan Francisco, CA$140K - 180KSenior
- 2 days agoLow ghost riskUberRemoteSan Francisco, CA$232K - 258KLead
- 2 days agoLow ghost riskPinterestOn-siteSan Francisco, CA$208K - 365KMid-level
- 14 hours agoLow ghost riskCrusoe EnergyOn-siteSan Francisco, CA$215K - 260KLead
- 14 hours agoLow ghost riskAnthropicOn-siteSan Francisco, CA$405K - 485KLead
- 1 day agoLow ghost riskSofiRemoteSan Francisco, CA$154K - 264KLead
- 4 days agoLow ghost riskAnthropicOn-siteSan Francisco, CA$405K - 485KLead
- 2 days agoLow ghost riskAnthropicOn-siteSan Francisco, CA$320K - 485KLead
- 2 days agoLow ghost riskUberHybridSan Francisco, CA$232K - 258KLead
- 2 days agoLow ghost riskAnthropicOn-siteSan Francisco, CA$405K - 485KLead
- 1 day agoLow ghost riskGoogle LLCOn-siteSan Francisco, CA$207K - 300KLead
- 14 hours agoLow ghost riskCrusoe EnergyOn-siteSan Francisco, CA$250K - 300KLead
- 1 day agoLow ghost riskGoogle LLCOn-siteSan Francisco, CA$207K - 300KLead
- 6 days agoLow ghost riskOneTrustOn-siteSan Francisco, CA$165K - 248KLead
- 6 days agoLow ghost riskOrbHybridSan Francisco, CA$160K - 220KLead
- 3 days agoLow ghost riskSnapchatOn-siteSan Francisco, CA$195K - 343KMid-level
- 14 hours agoLow ghost riskCrusoe EnergyOn-siteSan Francisco, CA$250K - 300KLead
- 14 hours agoLow ghost riskCrusoe EnergyOn-siteSan Francisco, CA$250K - 300KLead
- 1 day agoLow ghost riskCisco Systems, Inc.On-siteSan Francisco, CA$214K - 310KLead
Why this job matches
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Staff Software Engineer - AI Infra - Training
About the role and team
Leading at Uber means setting direction in motion, not waiting for perfect conditions. As a Staff Software Engineer, you will be a technical anchor for the foundational systems that move the world - from building the next generation of orchestration platforms to architecting the stacks that power our global applications. Our mission is to make transportation as reliable as running water, and we need technical powerhouses to build the dependable, high-performance foundation that supports that vision.
This is a role for a proven, large-scale systems thinker who thrives in high-stakes environments. You will navigate the "messy" reality of complex infrastructures spanning global data centers and multiple cloud providers, supporting a diverse variety of workloads. You'll need to make smart decisions with imperfect information and own the outcomes of global architectural choices. If you lead with clarity, build with heart, and are motivated by the challenge of peak efficiency at unparalleled scale - this is where you'll make your mark.
What you'll do
- Design and build end-to-end systems for Uber's ML training stack. Solve the scaling challenges on very large datasets and models.
- Provide deep technical mentorship across the stack, ensuring architecture and implementations are robust, extensible, and secure.
- Build innovative solutions that leverage statistical analysis to diagnose performance regressions and optimize resource utilization across complex infrastructures.
- Create best-in-class tools and frameworks that increase the velocity and quality of hundreds of internal engineering teams.
- Lead and mentor engineers, reviewing code and designs while fostering a culture of continuous learning and humility.
- Work cross-functionally with Product, Data Science, and Operations across the globe to drive large-scale projects and align technical investments with business value.
Basic Qualifications
- 8+ years of professional experience building scalable, fault-tolerant products or platforms, with a track record of solving strategically important problems.
- Proficiency in one or more programming languages (e.g., Go, C/C++, Java, Python, or JavaScript) and the ability to define organization-wide standards.
- Proficiency in state of the art deep learning technologies, such as distributed training frameworks, LLMs, GPU optimizations, etc.
- Proven experience leading large-scale engineering projects through the entire lifecycle from inception to global productionization.
- Expertise in making complex engineering/business tradeoffs, managing the implications of "buy vs. build" or "incremental vs. rewrite" decisions.
- Experience identifying architectural gaps and acting as a multiplier to reduce technical debt across the organization.
- Bachelor's degree in Computer Science, Engineering, Mathematics, or equivalent practical experience.
Preferred Qualifications
- Advanced degree (Master's or PhD) with a focus on distributed computing, system performance, or machine learning.
- Experience contributing to open-source projects or leading industry-level technical discussions.
- Ability to anticipate future business needs and develop extensible, modular designs that meet long-term scalability targets.
For San Francisco, CA-based roles: The base salary range for this role is USD $232,000 per year - USD $258,000 per year.
For Sunnyvale, CA-based roles: The base salary range for this role is USD $232,000 per year - USD $258,000 per year.
For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits.
Ready to Ride?
This isn't the kind of place where you follow a playbook - it's where you help write one. If you're driven by impact, energized by challenge, and ready to shape how the world moves - we'd love to hear from you.
You may be eligible for bonuses, equity, and other compensation, as well as a range of benefits. Explore our benefits.
Offices remain key to collaboration and Uber's culture. Unless approved for full remote work, employees must spend at least 50% of their time in-office. Some roles, like those at greenlight hubs, require full-time in-office presence. Ask your Recruiter for details about this role's requirements.
Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form.
Company Reviews
Employee reviews3.8
35,666 Reviews- Good place sonetime hectic2026-03-09T20:01:45.657
Pros: Pay, culture, smart people, impactful work
Cons: Sometimes hectic, slow growth. Nothing else
- Toxic in general, different by teams2026-03-09T08:32:26.780
Pros: Marketing team is great Push for innovation Fast paced
Cons: Ops team is toxic Politics is high Fast paced
- low pay2026-03-08T17:47:06.657
Pros: your own time work if you want
Cons: Not enough pay not enough requests
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Frequently asked questions about staff software engineer jobs in San Francisco
What is a ghost job?
A ghost job is a posting for a role the company isn't actively hiring for. Some stay up after the company fills the role. Others collect resumes for an opening that may never come.
You spend an evening tailoring an application, and nobody on the other side is looking for you.
What do staff software engineer jobs in San Francisco pay?
Across the postings here that list pay, the median is about $254,000 a year. Most of these postings list a pay range.
How many staff software engineer jobs in San Francisco are there?
At our last count there were about 500 open postings. The list on this page is live, so the count above it is the current one.
How does Enhancv spot a ghost job?
Every posting goes through five checks: how long it has been up, whether a salary is posted, what employees say about the company, how specific the description is and whether it lists real requirements. Each job shows the checks it passed and the ones it didn't.
How fresh are the job postings?
Enhancv checks postings every hour, and every job shows how long ago it went up. Most hires happen within 30 days of posting. A listing that's been open for two months raises its ghost job risk.










