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Software Engineer, Model Runtime

openai

Híbrido San Francisco
Development

Job Score

90 pts
Hybrid model (+80) Development (+10)

About the Team

OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform.

About the Role

You will build the model runtime within the inference engine that executes complex, frontier models at scale on OpenAI’s custom silicon. The runtime will sit between models running on the hardware and the upper layers of the cluster serving software stack, translating demanding inference workloads into efficient execution while optimizing for throughput, latency, utilization, and reliability.

You will work across model architecture, distributed systems, compilers, kernels, and silicon to design a production-grade runtime comparable in ambition to systems such as vLLM and SGLang, but customized and optimized for OpenAI’s AI accelerator. Your work will shape how new model capabilities map onto the platform and how quickly custom silicon can deliver meaningful performance in production.

In this role, you will:

  • Design and implement the LLM inference runtime for frontier models running on custom silicon.

  • Build scheduling, continuous batching, memory management, KV-cache management, and execution orchestration for high-performance inference.

  • Develop distributed execution strategies across chips, hosts, and racks, including model partitioning, communication, and synchronization.

  • Optimize end-to-end latency, throughput, memory efficiency, and hardware utilization across diverse model architectures and serving workloads.

  • Partner with kernel, compiler, architecture, and silicon teams to co-design interfaces and remove performance bottlenecks across the stack.

  • Enable new model features, execution patterns, numerical formats, and hardware capabilities in a reliable production runtime.

  • Create profiling, observability, benchmarking, and performance-modeling tools that make runtime behavior measurable and actionable.

  • Debug complex correctness, performance, and reliability issues spanning model code, runtime software, communication layers, and hardware.

  • Turn workload insights into clear requirements for future generations of silicon and system architecture.

You might thrive in this role if:

  • Have strong systems programming experience in C++, Rust, Python, or comparable performance-oriented environments.

  • Have built or optimized runtimes, distributed systems, compilers, kernels, model-serving infrastructure, or adjacent systems software.

  • Understand modern LLM inference, including prefill and decode behavior, batching, KV-cache tradeoffs, and model parallelism.

  • Can reason quantitatively about latency, throughput, compute intensity, memory bandwidth, communication, and utilization.

  • Are comfortable profiling and debugging performance across multiple layers of a hardware-software stack.

  • Can design clean abstractions while retaining the low-level control needed to extract performance from specialized hardware.

  • Work effectively across model, systems, compiler, kernel, and hardware teams to drive ambiguous technical problems to closure.

  • Care about production quality, including correctness, observability, reliability, maintainability, and graceful behavior at scale.

To comply with U.S. export control laws and regulations, candidates for this role may need to meet certain legal status requirements as provided in those laws and regulations.

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, and requests can be made via this link.

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.

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About Software Development

Software Development is one of the most dynamic and constantly evolving fields in the job market. Professionals in this area are responsible for creating, maintaining, and optimizing web, mobile, and desktop applications that impact millions of users daily.

Key languages and frameworks include JavaScript (React, Node.js, Vue.js), Python (Django, Flask), Java (Spring), PHP (Laravel), and TypeScript. Demand for full-stack developers continues to grow, especially in tech companies and startups.

Salaries range from entry-level to senior positions, with growing opportunities for remote work and international freelancing.

Discover Other Areas

Understand the scope of work, key skills, and tools used in different career areas.

About Systems Analyst

The Systems Analyst is the professional responsible for analyzing, designing, and implementing technology solutions that meet business needs. They act as a bridge between business areas and the development team, ensuring that systems deliver real value to the organization.

Key skills include requirements gathering and analysis, process modeling (BPMN), data modeling, technical and functional documentation, system integration (APIs, microservices), and knowledge of ERPs and CRMs. Tools like Jira, Confluence, Visio, and project management platforms are essential.

Systems Analysts in technology companies are highly valued, especially those who master agile requirements analysis (user stories, backlog), system integration, and solution architecture. The field offers opportunities from junior analyst to solution architect, with a focus on efficiency, quality, and technological innovation.

About Artificial Intelligence

Artificial Intelligence is currently the fastest-growing field in the technology market. The revolution in generative models (GPT, Claude, Gemini) has created massive demand for AI-specialized professionals.

Key areas of practice include Machine Learning Engineering, MLOps, Prompt Engineering, AI Research, and Applied AI. Python, TensorFlow, PyTorch, and LLM knowledge are essential skills.

AI salaries are the highest in the technology sector, with many remote work opportunities at international companies.

About Data

The Data field has undergone a radical transformation with the rise of Generative AI. Data professionals are fundamental for evidence-based decision-making across all industries.

Key specializations include Data Engineering, Data Science, Business Intelligence, Machine Learning Engineering, and Analytics. Tools like SQL, Python, Spark, dbt, and cloud platforms (AWS, GCP, Azure) are essential.

The data market continues with high demand and salaries among the most competitive in the technology sector, with many remote work opportunities.

About Tech Recruiter

The Tech Recruiter is a professional specialized in recruiting technology talent, from developers to AI engineers and DevOps professionals. They combine technical knowledge with recruitment skills to evaluate and attract highly qualified candidates.

Key skills include technical screening, analysis of technical profiles (GitHub, portfolios, blogs), knowledge of software stacks and architectures, networking in tech communities and events. Proficiency with tools like LinkedIn Recruiter, Gem, Ashby, and technical assessment platforms is a differentiator.

Tech Recruiters are scarce and highly paid professionals, especially those who can map and access passive talent in competitive markets like AI, data engineering, and cloud computing.

About Content Manager

The Content Manager is the professional responsible for leading the entire content strategy, production, and management of an organization. They define the editorial strategy, coordinate writing teams, and ensure content aligns with business goals and brand identity.

Key skills include content strategy, editorial planning, content audit, buyer persona, customer journey, content ops, content governance, performance metrics (ROI, engagement, organic traffic), and team management. Knowledge of WordPress, Contentful, Notion, and analytics tools is a differentiator.

Content Managers in technology companies are highly valued, especially those who can align content with conversion funnels, lead multidisciplinary teams, and use data to optimize editorial strategy. The field offers opportunities from content manager to head of content, with a focus on strategy, quality, and scale.

Career Guides

Technology Career Guide

Planning, skills, interviews, and professional growth in IT, Data Science, DevOps, and Product.

Read full guide →

Design Career Guide

UX/UI, Graphic Design, Product Design. Portfolio, tools, interviews, and growth in the Design field.

Read full guide →

Marketing Career Guide

SEO, Paid Media, Growth, Content Marketing. Certifications, tools, and strategies to grow in Digital Marketing.

Read full guide →

Finance Career Guide

Financial market, investments, corporate finance, certifications, and strategies to grow in the financial field.

Read full guide →

Communication Career Guide

Journalism, PR, Corporate Communication, Content Marketing, and Multimedia Production.

Read full guide →

Administration Career Guide

Business Management, HR, Logistics, Consulting, Project Management, and Entrepreneurship.

Read full guide →

Data Career Guide

Data Science, Data Engineering, BI, Machine Learning, and AI. From training to the job market.

Read full guide →

Product Career Guide

Product Management, Product Ownership, Agile, Scrum, and OKRs. From strategy to execution.

Read full guide →

Tech & Remote Glossary

Stop getting lost in interviews and job descriptions

The job market, especially within tech and global companies, has developed its own dialect. Not understanding these acronyms can make you lose valuable opportunities or poorly negotiate your contract. To end this problem, we created the Definitive Glossary for the Remote Professional.

🏢 Work Models & Routine

Async (Asynchronous Work)
A communication model where responses don't need to be immediate. Instead of back-to-back meetings, the team relies on well-structured documents, threads, and messages. It's the gold standard for global companies spanning multiple time zones.
Sync (Synchronous Work)
The opposite of Async. It requires the team to be online and available at the same time for meetings, live chats, and real-time collaboration.
Daily / Stand-up
A quick daily meeting (usually 15 minutes) common in Agile (Scrum) methodologies. The team answers three questions: What did I do yesterday? What will I do today? Are there any blockers?
All-Hands / Town Hall
A company-wide meeting involving all employees. Usually led by the founders (C-Levels) to present results, new goals, and answer team questions.
1:1 (One-on-One)
A recurring individual meeting between a professional and their direct manager. It is used for career alignment, feedback, and problem-solving, not just for project status updates.

💰 Contracts, Benefits & Compensation

PTO (Paid Time Off)
Instead of strict, categorized leave policies, modern US companies usually offer a flexible pool of days (e.g., 20 days of PTO, or even "Unlimited PTO") that you can use for vacations, sick days, or personal matters, while receiving your regular compensation.
Equity / Stock Options
Company ownership. The startup offers you the right to buy shares at a heavily discounted strike price in the future. If the company grows, goes public, or is acquired, these shares can be highly lucrative.
Vesting (Vesting Schedule)
The rule that controls your Equity. It usually lasts 4 years. You don't get all the shares on day one; you "earn" them gradually as you stay with the company. A "1-year Cliff" means you must stay for at least one year to receive your first batch of shares.
RSUs (Restricted Stock Units)
Unlike Stock Options (where you have the right to buy the stock), RSUs are actual shares the company grants you as a bonus or part of your compensation package, following a strict Vesting schedule.
Independent Contractor (1099 / B2B)
The most common international hiring model for global talent working for US companies. You act as a service provider (business-to-business), receiving the gross salary (often six-figure compensation) without standard local payroll tax deductions at the source.

🤖 Recruitment & Hiring Process

ATS (Applicant Tracking System)
The "robot" that reads your resume. Software like Greenhouse, Ashby, and Workday are used to filter candidates by keywords before a human even looks at the document. (Pro tip: this is why your resume must be clean, semantic, and have the right keywords).
JD (Job Description)
The document that lists the responsibilities, technical requirements, and benefits of the open position.
Cultural Fit
The interview stage that evaluates if your core values, communication style, and worldview align with the company's culture. This is the ultimate test of your Soft Skills.
Onboarding
The integration process. It's the period of your first few weeks at the company, where you get your access credentials, learn about the culture, study the internal documentation, and understand how the product works.

🚀 How to use this to your advantage?

The secret isn't just knowing what these acronyms mean, but using them actively. If during an interview for a premium tech role you ask, "How does your PTO policy and Vesting schedule work?", the recruiter will immediately perceive you as a high-level professional, familiar with the global market standards.

The remote job market requires preparation. And having the right vocabulary is the first big step to securing six-figure proposals and standing out among thousands of applicants.

Expert Tip

Data-Driven: How Data Defines Company Success or Failure

The Data-Driven Era: How Data Culture Defines Company Success or Failure

Published by Mondywork | Category: Data / Business Intelligence

The End of Corporate Gut Feeling

In the past, major business decisions were made based on intuition, previous experience, or the famous "gut feeling" of directors (what the market refers to as the HiPPO - Highest Paid Person's Opinion). Today, however, in a highly competitive and globalized corporate ecosystem, relying on guesswork is the fastest recipe for bankruptcy.

Digital transformation didn't just connect processes; it generated a massive volume of information. The companies that thrive are those that know how to capture, clean, and transform this raw data into actionable insights.

"Data-driven organizations are 23 times more likely to acquire customers, six times as likely to retain those customers, and 19 times as likely to be profitable as a result."
— McKinsey Global Institute Study

What Does it Mean to Have a Data-Driven Culture?

Being Data-Driven doesn't just mean subscribing to expensive Analytics tools or having a beautiful dashboard on the office wall. It's a fundamental shift in organizational culture, where truth is sought in the numbers before any action is executed.

  • Predictability: Predictive models allow companies to forecast market trends, customer churn, and operational bottlenecks before they happen.
  • Risk Mitigation: Decisions based on statistics drastically reduce the margin of error in investments and new product launches.
  • Personalization at Scale: Behavioral analysis enables marketing to deliver exactly what the user wants, right when they have the highest propensity to buy.

The Impact of Business Intelligence (BI) and Big Data

To extract the true value from information, companies are building robust Business Intelligence (BI) and Big Data departments. ETL (Extract, Transform, Load) processes, Data Lakes architecture, and the mastery of software like Power BI and Tableau have become the backbone of top-tier US startups and unicorns.

The Harvard Business Review has repeatedly highlighted that the professional who can translate complex data into business language is a modern corporation's most valuable asset. It's not enough to have the data; you must know how to tell a story with it (Data Storytelling).

The Job Market: The Hunt for Data Talent

With this paradigm shift, the demand for Data Engineers, BI Analysts, Data Scientists, and Analytics Engineers has skyrocketed. International companies—especially in the US and Europe—are aggressively hiring global professionals for 100% US Remote roles, offering highly competitive six-figure compensation packages.

For these companies, which use rigorous Applicant Tracking Systems (ATS like Ashby, Workday, and Greenhouse), the ideal candidate is one who seamlessly blends technical mastery (SQL, Python, DAX) with a sharp business acumen.


References and Recommended Reading

  • McKinsey & Company: The data-driven enterprise of 2025.
  • Harvard Business Review: How to Build a Data-Driven Culture.
  • Gartner: Top Trends in Data and Analytics.

Master the art of turning data into revenue?

The best US startups and global tech companies are actively looking for analytical professionals like you, offering remote roles with premium compensation. Don't miss out on the top Data, BI, and Machine Learning opportunities in the market.