network engineer

Lambda

<div>Lambda, The Superintelligence Cloud, is a leader in AI cloud infrastructure serving tens of thousands of customers. Our customers range from AI researchers to enterprises and hyperscalers. Lambda's mission is to make compute as ubiquitous as electricity and give everyone the power of superintelligence. One person, one GPU.
If you'd like to build the world's best AI cloud, join us.<ul><li>Note: This position requires presence in our San Francisco/San Jose office location 4 days per week; Lambda&rsquo;s designated work from home day is currently Tuesday.</li></ul>
What You&rsquo;ll Do<ul><li>
Help to build and scale Lambda's high performance cloud network</li><li>
Work on deploying and configuring networking Hardware for new and existing clusters</li><li>
Ensure high availability of our network through monitoring, failover, and redundancy</li><li>
Contribute to automation of network configuration management and operation</li><li>
Work with internal and external customers to resolve network related issues</li><li>
Help with deploying and maintaining network monitoring and management tools</li><li>
Will be part of day2 operations and on-call rotation for Network Engineering team</li></ul>
You<ul><li>
Have 10+ years of experience in IT and networking space</li><li>
Have 6+ years of experience in designing and operating production Data Center type of networks</li><li>
Have led the implementation of large production-scale networking projects</li><li>
Experience managing Next-Generation Firewalls (e.g. Fortigate)</li><li>
Have experience with cloud providers networking (such as AWS, GCP, OCI)</li><li>
Expert in CLOS/Spine and Leaf fabrics,EVPN/VXLAN, ECMP, BGP, and fast convergence techniques.</li><li>
Are comfortable on the Linux command line, and have an understanding of the Linux networking stack and internals</li><li>
Strong automation skills (Python, Ansible) and network APIs and worked with git or similar source control systems</li><li>
Production experience with multiple network gear vendors (Arista, Juniper, Cisco, Cumulus/SONiC, Opengear)</li><li>
Experience with Networking Monitoring stack (Datadog, Clickhouse, Grafana, Prometheus, gNMI, OTel)</li></ul>
Nice to Have<ul><li>
Have knowledge or experience maintaining Software Defined Networks (SDN)</li><li>
Experience automating network configuration within public clouds, with tools like Terraform/Ansible/Salt</li><li>
Hands-on with HPC/AI networking: RoCEv2 and/or InfiniBand (Congestion Control, VLs, partitions), GPUDirect RDMA concepts.</li><li>
Experience with DWDM technologies and SD-WAN</li><li>
Understanding of data center power/space/cooling trade-offs and their impact on topology choices</li><li>
Have experience with virtualization technology, like ESXi, KVM, and VMs management</li><li>
Experience with LoadBalancers like F5, NetScaler</li></ul>
Salary Range Information
The annual salary range for this position has been set based on market data and other factors. However, a salary higher or lower than this range may be appropriate for a candidate whose qualifications differ meaningfully from those listed in the job description.
About Lambda<ul><li>
Founded in 2012, with 500+ employees, and growing fast</li><li>
Our investors notably include TWG Global, US Innovative Technology Fund (USIT), Andra Capital, SGW, Andrej Karpathy, ARK Invest, Fincadia Advisors, G Squared, In-Q-Tel (IQT), KHK &amp; Partners, NVIDIA, Pegatron, Supermicro, Wistron, Wiwynn, Gradient Ventures, Mercato Partners, SVB, 1517, and Crescent Cove</li><li>
We have research papers accepted at top machine learning and graphics conferences, including NeurIPS, ICCV, SIGGRAPH, and TOG</li><li>
Our values are publicly available: https://lambda.ai/careers</li><li>
We offer generous cash &amp; equity compensation</li><li>
Health, dental, and vision coverage for you and your dependents</li><li>
Wellness and commuter stipends for select roles</li><li>
401k Plan with 2% company match (USA employees)</li><li>
Flexible paid time off plan that we all actually use</li></ul>
A Final Note:
You do not need to match all of the listed expectations to apply for this position. We are committed to building a team with a variety of backgrounds, experiences, and skills.
Equal Opportunity Employer
Lambda is an Equal Opportunity employer. Applicants are considered without regard to race, color, religion, creed, national origin, age, sex, gender, marital status, sexual orientation and identity, genetic information, veteran status, citizenship, or any other factors prohibited by local, state, or federal law.
Compensation Range: $278K - $417K</div>

Network Engineer

FluidStack

<div><div><div>San Francisco, CA,Austin, TX,New York, NY
 </div></div><div>Full Time</div></div>
 <div><h1 class="jobSectionHeader">About Fluidstack</h1>
At Fluidstack, we build the compute, data centers, and power that will fuel artificial superintelligence. We supply GWs of compute capabilities to the world&rsquo;s biggest AI Labs at industry-defining speeds.
Our team is small, fast, and obsessed with quality. We own outcomes end-to-end, challenge assumptions, and treat our customers' problems as our own. No task is beneath anyone here.
There are a few thousand people who will shape the trajectory of superintelligence. Come and be one of them.
<h1 class="jobSectionHeader">About the Role</h1>
We are looking for a Network Engineer, WAN to architect and operate the global network backbone connecting Fluidstack&rsquo;s data centers and GPU clusters. You will be responsible for designing high-performance, secure, and reliable wide-area networks (WANs) to support data movement across regions. You will work closely with our compute, storage, infrastructure, and facility teams to ensure seamless, low-latency connectivity across our infrastructure footprint.
<h1 class="jobSectionHeader">Focus</h1>
<ul><li>Architect, implement, and maintain high-throughput, low-latency WAN links across data center sites.
</li><li>Experience with optical transport (DWDM, ROADM, coherent optics) and platforms such as Ciena
</li><li>Lead carrier engagements end-to-end: circuit procurement, contract negotiation, SLA management, and escalation
</li><li>Monitor and optimize interconnect performance, including routing, packet loss, and bandwidth usage.
</li><li>Coordinate physical fiber entries, cross-connects, and demarcation points with ICT and facility teams
</li><li>Develop and maintain WAN capacity models; forecast bandwidth needs aligned to deployment roadmap
</li><li>Automate configuration, provisioning, and monitoring of WAN infrastructure.
</li><li>Deploy and maintain site-to-site VPNs, private peering, and direct connects with hyperscalers.
</li><li>Troubleshoot complex network issues.
</li><li>Implement best practices for redundancy, failover, and disaster recovery.
</li><li>Collaborate with infrastructure engineering, SREs, and software teams.
</li><li>Support future growth by contributing to global network expansion plans. 
</li></ul><h1 class="jobSectionHeader"> 
About You
</h1><ul><li>7+ years of experience in network infrastructure engineering with a focus on WAN design and operations.
</li><li>Deep understanding of network routing protocols (BGP, OSPF), MPLS, and IPsec VPNs.
</li><li>Strong documentation habits; ability to create runbooks, topology diagrams, and decision records
</li><li>Proven experience with fiber, transport circuits, and carrier peering arrangements.
</li><li>Strong knowledge of Linux networking and systems administration.
</li><li>Experience with infrastructure automation (e.g., Ansible, Terraform, NetBox).
</li><li>Familiarity with monitoring and telemetry tools (e.g., Grafana, Prometheus, ELK, or custom tooling).
</li><li>Ability to manage projects across multiple sites and time zones.
</li><li>Excellent written and verbal communication skills. 
</li></ul><h1 class="jobSectionHeader"> 
Salary &amp; Benefits
</h1><ul><li>Competitive total compensation package (salary + equity).
</li><li>Retirement or pension plan, in line with local norms.
</li><li>Health, dental, and vision insurance.
</li><li>Generous PTO policy, in line with local norms. 
 
</li></ul>The base salary range for this position is $150,000 - $300,000 per year, depending on experience, skills, qualifications, and location. This range represents our good faith estimate of the compensation for this role at the time of posting. Total compensation may also include equity in the form of stock options.
We are committed to pay equity and transparency.
Fluidstack is an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability and protected veterans&rsquo; status, or any other characteristic protected by law. Fluidstack will consider for employment qualified applicants with arrest and conviction records pursuant to applicable law.
You will receive a confirmation email once your application has successfully been accepted. If there is an error with your submission and you did not receive a confirmation email, please email careers@fluidstack.io with your resume/CV, the role you've applied for, and the date you submitted your application- someone from our recruiting team will be in touch.</div>

Network Engineer, WAN

<div><div><div>San Francisco, CA,Austin, TX,San Francisco, CA
 </div></div><div>Full Time</div></div>
 <div><h1 class="jobSectionHeader">About Fluidstack</h1>
At Fluidstack, we build the compute, data centers, and power that will fuel artificial superintelligence. We supply GWs of compute capabilities to the world&rsquo;s biggest AI Labs at industry-defining speeds.
Our team is small, fast, and obsessed with quality. We own outcomes end-to-end, challenge assumptions, and treat our customers' problems as our own. No task is beneath anyone here.
There are a few thousand people who will shape the trajectory of superintelligence. Come and be one of them.
<h2 class="jobSectionHeader">About the Role</h2>
Fluidstack is seeking a Network Engineer, Reliability &amp; Observability to serve as a reliability engineer championing and building process, data collections, and reliability metrics with the objective of improving the quality and reliability of AI networks from deployment through the full lifecycle of operations.
This role is focused on developing processes, systems, tools, data and data pipelines, and observability to improve the quality of networks and deliver automated metrics (24x7) as well as periodic reliability reports for both internal and external customers.
This role is ideal for experienced network operators who are passionate about reliability and have experience designing and building full lifecycle software such as Quality Assurance audits, circuit audits, periodic audits, failure rates and failure analysis. You are passionate about hardware (electronics and optics), software development, and you value and promote the use of data to make informed decisions in deployment, operations, and strategic sourcing.
Experienced SRE (Site Reliability Engineers) with a passion for networking are encouraged to apply. 
 
<h2 class="jobSectionHeader">Focus</h2>
<ul><li>Ownership of Quality Assurance: Design, develop, and support QA process for network hardware and networks.
</li><li>Pipelines: Develop and deploy serverless workflows, server based, and manually triggered data pipelines producing network quality and reliability observability for internal and external customers.
</li><li>Deployment and Operations Support: Support full lifecycle data collection and analysis partnering with Deployment, Operations, DC hardware, and logistics teams to produce data that drives process improvements and delivers on SLA and SLOs.
</li><li>Process Engineering: Develop, pilot, and deploy process improvements for deployment and repair to produce data and consume data with Machine Learning to fulfill our mission.
</li><li>Cross-Team Collaboration: Own without ego and execute in a collaborative team with design, deployment, operations engineers and software developers.
</li><li>Subject Matter Expert: In at least two or more deep subjects such as IP routing, optics, optical transport, Ethernet, RDMA/RoCE, or electrical power. 
 
</li></ul><h2 class="jobSectionHeader">About You</h2>
<ul><li>Strong Operations Background: 5+ years in network engineering and at least 3+ years in operations with significant hands-on operational experience. You've run production networks or compute, responded to incidents at all hours, and debugged complex failures under pressure. You understand the difference between &quot;working&quot; and &quot;production-ready&quot;.
</li><li>Software Development: You have experience with ITIL, Agile (xP), and TDD including developing and leading programs and projects. You have experience building hyperscale platforms, demonstrating a fluency in Golang with supporting tools in Python or RUST.
</li><li>Datacenter Fabric Expertise: Deep experience operating modern datacenter networks including EVPN/VXLAN, BGP, CLOS topologies, and high-radix switching. You're comfortable troubleshooting Layer 2/3 issues, BGP routing problems, fabric misconfigurations, and physical media failures..
</li><li>Incident Response Excellence: Proven ability to lead incident response, perform systematic troubleshooting, and drive issues to resolution. You remain calm during outages, communicate clearly with stakeholders, and know when to escalate versus when to dig deeper. You've been the person others call when things break.
</li><li>Matrix Leadership Experience: You understand how to build relationships with onsite teams, coordinate physical infrastructure work, and represent network engineering in a field environment. You know how to get things done in operational settings with many internal and external teams and stakeholders.
</li><li>Operational Pragmatism: You balance perfection with progress. You can troubleshoot with imperfect information, make pragmatic decisions under time pressure, and prioritize based on business impact. You document as you go and continuously improve operational processes.
</li><li>Self Driven: You embrace complex challenges with undefined process and key results. You can dive in to learn, but zoom back out to build Objectives, develop Key Results and build a software development project and pipeline in Jira solo. You can then switch hats and begin coding.
</li><li>Travel: You are willing and able to travel to spend time with the team at our local offices or data center locations, up to 20% of the time. 
 
</li></ul><h2 class="jobSectionHeader">Nice to Haves</h2>
<ul><li>AI/HPC Fabric Operations: Experience operating AI/ML or HPC fabrics with RDMA (RoCEv2), lossless Ethernet (PFC, ECN), or high-performance networking. You understand the operational precision required when network performance directly impacts workload completion.
</li><li>Reliability Engineering: You have experience with observability and reliability engineering from network operations or in manufacturing quality.
</li><li>Hardware Repair Experience: Hands-on experience coordinating hardware repairs, RMAs, and physical infrastructure work. You understand datacenter logistics, vendor escalation processes, and how to work effectively with onsite technicians.
</li><li>Observability &amp; Monitoring: Familiarity with network monitoring platforms, alerting systems, and telemetry collection. You've used monitoring tools to diagnose issues proactively and tune alerting to reduce noise. You have experience with SQL, MySQL, and building operations dashboards. 
 
</li></ul><h2 class="jobSectionHeader">Salary &amp; Benefits</h2>
<ul><li>Competitive total compensation package (salary + equity).
</li><li>Retirement or pension plan, in line with local norms.
</li><li>Health, dental, and vision insurance.
</li><li>Generous PTO policy, in line with local norms. 
 
</li></ul>The base salary range for this position is $150,000 - $250,000 per year, depending on experience, skills, qualifications, and location. This range represents our good faith estimate of the compensation for this role at the time of posting. Total compensation may also include equity in the form of stock options.
We are committed to pay equity and transparency.
Fluidstack is an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability and protected veterans&rsquo; status, or any other characteristic protected by law. Fluidstack will consider for employment qualified applicants with arrest and conviction records pursuant to applicable law.
You will receive a confirmation email once your application has successfully been accepted. If there is an error with your submission and you did not receive a confirmation email, please email careers@fluidstack.io with your resume/CV, the role you've applied for, and the date you submitted your application- someone from our recruiting team will be in touch.</div>

Network Engineer, Reliability & Observability

Meter

<div>
 Why this role exists
 
 
 Network engineers carry the most valuable signal in the world in their heads, and it disappears the moment they close a ticket.
 
 
 Your job is to build the system that captures that signal so that our models can learn to think like network engineers.
 
 
 If you get this right, Meter can manage thousands of customers&rsquo; networks autonomously, without adding a single engineer.
 
 
 The problem you&rsquo;re walking into
 
 
 LLMs are good at code because of their access to Git. Commit messages explain why a change was made, PR threads capture expert disagreement, issue trackers record dead ends and eventual fixes. Models trained on that corpus of data don&rsquo;t just pattern-match, they&rsquo;ve seen millions of examples of human reasoning through problems.
 
 
 Network engineering has none of this. When a network engineer looks at a set of device stats and figures out it&rsquo;s upstream packet loss &mdash; not a hardware failure, not a misconfiguration, specifically upstream packet loss &mdash; that reasoning lives in their head. Never in a place a model can learn from.
 
 
 You will build the Git and Github for network engineering. A structured, queryable record of what the network looked like, what the expert notice, and why they made the call they made.
 
 
 What you will ship
 
 
 First 30 days
 
 
 Sit with our network engineers and watch how they work. Don&rsquo;t touch code yet. Understand what a great diagnostic reasoning record actually looks like and what data you&rsquo;ll need to build one. Map the existing landscape: telemetry in ClickHouse, configs in Postgres, support history in Salesforce.
 
 
 60 days in
 
 
 Ship a working v1 of the annotation interface. Network engineers should be able to open a historical support ticket, see what the network looked like at the time of the incident, and log their diagnostic reasoning against it. It doesn&rsquo;t have to be elegant, it has to be useful enough for engineers to want to use it.
 
 
 90 days in
 
 
 Our network engineers are generating training data independently without engineering support. The first model benchmarks built from the pipeline are running and you can point to a number knowing the model improved because of what you shipped.
 
 
 Tech Stack
 
 
 TypeScript, React, Go, GraphQL, Kafka, Postgres.
 
 
 Who you&rsquo;ll work with
 
 
 Our co-founder and CEO will lead the product roadmap.
 
 
 In addition to your customers, network engineers, you&rsquo;ll partner closely with two research engineers who have deep ML backgrounds and a clear picture of what training data needs to look like. They&rsquo;re excited to have a partner in building the app.
 
 
 Measuring success
 
 
 <ul>
 <li>
 Within 90 days, Network engineers are generating training data independently, without pinging you
 </li>
 <li>
 We have a large set of high-quality annotated cases in the pipeline
 </li>
 <li>
 Model benchmark scores are moving in the right direction because of the data this pipeline produced
 
 
 </li>
 </ul>
 What we&rsquo;re looking for
 
 
 You&rsquo;ve built backend systems end-to-end and made real architectural decisions with real consequences. You have opinions about data storage that come from having made the wrong decisions.
 
 
 You have deep customer empathy. You&rsquo;ll spend your first weeks learning how network engineers think and work. This knowledge will shape your future decisions.
 
 
 You care about people using the tools you built for them. Network engineer tool adoption and satisfaction leads to critical training data, model improvement, and eventually autonomous networks.
 
 
</div>

Software Engineer, Models

<div><div>San Francisco, CA
 </div><div>Full Time</div></div>
 <div><h1 class="jobSectionHeader">About Fluidstack</h1>
At Fluidstack, we build the compute, data centers, and power that will fuel artificial superintelligence. We supply GWs of compute capabilities to the world&rsquo;s biggest AI Labs at industry-defining speeds.
Our team is small, fast, and obsessed with quality. We own outcomes end-to-end, challenge assumptions, and treat our customers' problems as our own. No task is beneath anyone here.
There are a few thousand people who will shape the trajectory of superintelligence. Come and be one of them.
<h1 class="jobSectionHeader">About the Role</h1>
As a System Engineer, GPU Fleet, you will manage, operate, and optimize hyperscale GPU compute infrastructure supporting AI/ML training and inference workloads. Ensure high availability, performance, and reliability of GPU server fleet through automation, monitoring, troubleshooting, and collaboration with hardware engineering, platform teams, and datacenter operations.
<h2 class="jobSectionHeader">Focus</h2>
<ul><li>Operate and maintain large-scale GPU server fleet (H100, B200, GB200) supporting AI/ML workloads; monitor system health, performance, and utilization to maximize uptime and ensure SLA compliance
</li><li>Perform hands-on troubleshooting and root cause analysis of complex hardware, firmware, OS, and application issues across GPU clusters; coordinate with vendors and hardware teams to resolve systemic failures
</li><li>Develop and maintain automation scripts for provisioning, configuration management, monitoring, and remediation at scale.
</li><li>Build and improve tooling for GPU health checks, performance diagnostics, driver validation, and automated recovery
</li><li>Execute server provisioning, configuration, firmware updates, and OS installation using automation frameworks; manage lifecycle operations including deployment, maintenance, and decommissioning
</li><li>Participate in 24x7 on-call rotation; respond to production incidents and coordinate resolution with cross-functional teams including datacenter operations, network engineering, and application teams
</li><li>Lead post-incident reviews, document root causes, and drive continuous improvement initiatives focused on automation, reliability, monitoring, and operational efficiency 
</li></ul><h1 class="jobSectionHeader"> 
Basic Qualifications
</h1><ul><li>Bachelor's degree in Computer Science, Engineering, or related technical field (or equivalent practical experience)
</li><li>3+ years (System Engineer) or 5+ years (Senior System Engineer) in Linux system administration, datacenter operations, or infrastructure engineering
</li><li>Strong Linux/Unix fundamentals including system administration, shell scripting (Bash, Python), troubleshooting, and performance tuning
</li><li>Experience with server hardware architecture, troubleshooting techniques, and understanding of compute, memory, storage, and networking components
</li><li>Experience in automation and configuration management tools (Ansible, Puppet, Chef, Terraform).
</li><li>Strong analytical and problem-solving skills with ability to diagnose complex technical issues under pressure
</li><li>Excellent communication and collaboration skills; ability to work effectively with cross-functional teams
</li></ul><h1 class="jobSectionHeader">Preferred Qualifications</h1>
<ul><li>Experience managing large-scale GPU infrastructure (NVIDIA H100, A100, B200, GB200) in production environments supporting AI/ML workloads
</li><li>Deep knowledge of GPU architecture, CUDA toolkit, GPU drivers, monitoring tools (nvidia-smi, DCGM)
</li><li>Experience with HPC cluster management, job schedulers (Slurm, PBS, LSF), and container orchestration (Kubernetes, Docker)
</li><li>Proficiency in out-of-band management protocols (IPMI, Redfish, BMC) and firmware management for server hardware
</li><li>Experience with high-performance networking (InfiniBand, RoCE, RDMA) and network troubleshooting in GPU cluster environments
</li><li>Familiarity with datacenter operations including rack installations, cabling, power management, and thermal considerations 
 
</li></ul><h1 class="jobSectionHeader">Salary &amp; Benefits</h1>
<ul><li>Competitive total compensation package (salary + equity).
</li><li>Retirement or pension plan, in line with local norms.
</li><li>Health, dental, and vision insurance.
</li><li>Generous PTO policy, in line with local norms.
</li></ul>The base salary range for this position is $200,000 - $300,000 per year, depending on experience, skills, qualifications, and location. This range represents our good faith estimate of the compensation for this role at the time of posting. Total compensation may also include equity in the form of stock options.
We are committed to pay equity and transparency.
Fluidstack is an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability and protected veterans&rsquo; status, or any other characteristic protected by law. Fluidstack will consider for employment qualified applicants with arrest and conviction records pursuant to applicable law.
You will receive a confirmation email once your application has successfully been accepted. If there is an error with your submission and you did not receive a confirmation email, please email careers@fluidstack.io with your resume/CV, the role you've applied for, and the date you submitted your application- someone from our recruiting team will be in touch.</div>

System Engineer, GPU Fleet

OpenAI

About the Team
 
We’re hiring software engineers to make OpenAI’s networking teams more productive. These teams build and operate the high-performance networking systems that support OpenAI’s training and inference infrastructure at frontier scale.
 
About the Role
 
We’re looking for someone who cares deeply about the developer experience of engineers working on complex infrastructure systems — especially around build systems, test architecture, release pipelines, and reliable development workflows.
 
This role will be embedded with OpenAI’s networking team: making it faster, safer, and easier for engineers to build, test, validate, and ship changes across multi-server, networked, and hardware-adjacent environments.
 
In this role you will: 
Improve development workflows for engineers building and operating OpenAI’s networking systems
 
Design and improve continuous deployment, release, and validation pipelines
 
Build and maintain test harnesses for multi-server, networked, and hardware-backed environments
 
Improve iteration speed across C++, Python, and build-system-heavy codebases
 
Partner with engineers to identify friction in CI, testing, debugging, and deployment workflows
 
Drive testing and reliability strategy for infrastructure components that support large-scale training and inference workloads
 
Work closely with centralized developer experience teams while staying deeply embedded with the networking engineers closest to the systems
 
You might thrive in this role if: 
You are motivated by helping other engineers move faster and with more confidence
 
You have experience with CI/CD, release pipelines, testing infrastructure, or build systems
 
You are comfortable moving between C++, Python, and build systems such as CMake, Bazel, or Blaze
 
You enjoy building test harnesses, automation, and workflow improvements for complex systems
 
You do not need to be a networking expert, but you are excited to learn enough about the domain to make the team meaningfully more effective
 
When you see repeated friction — slow builds, flaky tests, brittle release processes, painful debugging, unclear validation — your instinct is to fix the underlying system
 
You are pragmatic and know how to balance high standards with forward progress
 
You like going end-to-end: understanding the engineers, the workflows, the codebase, and the operational realities behind the system
 
You are self-directed and comfortable operating with ambiguity in a high-context infrastructure environment
 
About OpenAI
 
OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.
 
We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
 
For additional information, please see
 
OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement
 
.
 
Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.
 
To notify OpenAI that you believe this job posting is non-compliant, please submit a report through
 
this form
 
. No response will be provided to inquiries unrelated to job posting compliance.
 
We are committed to providing reasonable accommodations to applicants with disabilities.
 
OpenAI Global Applicant Privacy Policy
 
At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.
 
Compensation
 
$230K – $385K

Software Engineer, Productivity - Networking

Handshake

<div>
 
 About Handshake
 
 
 
 Handshake is the career network for the AI economy. 20 million knowledge workers, 1,600 educational institutions, 1 million employers (including 100% of the Fortune 50), and every foundational AI lab trust Handshake to power career discovery, hiring, and upskilling, from freelance AI training gigs to first internships to full-time careers and beyond. This unique value is leading to unparalleled growth; in 2025, we tripled our ARR at scale.
 
 
 
 Why Join Handshake Now
 
 
 
 <ul>
 <li>
 Shape how every career evolves in the AI economy, at global scale, with impact your friends, family and peers can see and feel
 </li>
 <li>
 Work hand-in-hand with world-class AI labs, Fortune 500 partners and the world&rsquo;s top educational institutions
 </li>
 <li>
 Join a team with leadership from Scale AI, Meta, xAI, Notion, Coinbase, and Palantir, among others
 </li>
 <li>
 Build a massive, fast-growing business with billions in revenue
 
 
 </li>
 </ul>
 
 About The Role
 
 
 
 We&rsquo;re hiring a
 
 Software Engineer
 
 to build our Reinforcement Learning Environments (RLE) platform&mdash;the interactive systems where frontier AI models learn to complete real-world work.
 
 
 This role owns meaningful components end-to-end and plays a key part in scaling systems that power model training and evaluation.
 
 
 
 Location:
 
 San Francisco, CA (in-office, 5 days/week)
 
 
 What You&rsquo;ll Do
 
 
 <ul>
 <li>
 Build and scale core components of RLE environments and infrastructure
 </li>
 <li>
 Design and implement backend systems and data pipelines
 </li>
 <li>
 Translate ambiguous product and research needs into production systems
 </li>
 <li>
 Develop modular, reusable workflow domains
 </li>
 <li>
 Improve reliability, observability, and system performance
 
 
 </li>
 </ul>
 What We&rsquo;re Looking For
 
 
 <ul>
 <li>
 2&ndash;4 years of experience in backend, distributed systems, or ML-adjacent infrastructure
 </li>
 <li>
 Strong proficiency in ReactJS and TypeScript
 </li>
 <li>
 Solid experience with relational databases (PostgreSQL) and data modeling
 </li>
 <li>
 Experience with cloud infrastructure (AWS/GCP) and CI/CD
 </li>
 <li>
 Ability to independently drive projects from design to production
 
 
 </li>
 </ul>
 Nice to Have
 
 
 <ul>
 <li>
 Experience with simulation systems or evaluation platforms
 </li>
 <li>
 Exposure to ML systems or working with research teams
 </li>
 <li>
 Experience in fast-moving, operations-heavy environments
 
 
 </li>
 </ul>
 What Success Looks Like
 
 
 <ul>
 <li>
 Owns and delivers key RLE components end-to-end
 </li>
 <li>
 Improves system scalability and developer velocity
 </li>
 <li>
 Enables faster launch of new domains with high-quality data
 
 
 </li>
 </ul>
 
 Perks
 
 
 
 Handshake delivers benefits that help you feel supported&mdash;and thrive at work and in life.
 
 
 The below benefits are for full-time US employees.
 
 
 🎯 Ownership: Equity in a fast-growing company
 
 
 💰 Financial Wellness: 401(k) match, competitive compensation, financial coaching
 
 
 🍼 Family Support: Paid parental leave, fertility benefits, parental coaching
 
 
 💝 Wellbeing: Medical, dental, and vision, mental health support, $500 wellness stipend
 
 
 📚 Growth: $2,000 learning stipend, ongoing development
 
 
 💻 Office: Commuting support, free lunch, and gym in our SF office
 
 
 🏝 Time Off: Flexible PTO, 15 holidays + 2 flex days
 
 
 🤝 Connection: Team outings &amp; referral bonuses
 
 
 Compensation Range: $157.5K - $175K
 
 
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Software Engineer I, RLE

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