Researcher, Training Careers at OpenAI - San Francisco, California | Apply Now!
OpenAI
Researcher, Training Careers at OpenAI - San Francisco, California | Apply Now!
Job Description
Researcher, Training Careers at OpenAI - San Francisco, California | Apply Now!
Role Overview
Join OpenAI's elite Training team as a Researcher, Training in San Francisco, California, and become a key architect behind the world's most advanced large language models (LLMs). This senior-level role places you at the forefront of AI innovation, where you'll design, prototype, and scale groundbreaking architectures that power flagship models like GPT-4o, o1-mini, and future AGI systems. OpenAI's Training team is the powerhouse producing LLMs that drive research, products, and humanity's progress toward artificial general intelligence (AGI).
In this high-impact position, you'll combine deep research into architectures, datasets, and optimization with bold long-term bets on model efficiency and capabilities. Expect to integrate cutting-edge techniques into production model artifacts used company-wide. Ideal for researchers with hands-on experience in LLM development, this hybrid role (3 days/week in-office) offers relocation support and the chance to work alongside the brightest minds in AI.
The role demands a sophisticated grasp of model inference, empirical rigor, and versatility—from creative breakthroughs to baseline strengthening, eval design, regression debugging, and bottleneck hunting. If you're passionate about safely deploying world-class LLMs, this is your opportunity to shape the future of AI at OpenAI.
Key Responsibilities
As a Researcher, Training at OpenAI, your contributions will directly elevate model intelligence, efficiency, and new capabilities. Here's what you'll tackle daily:
- Design Novel Architectures: Innovate new model architectures to boost intelligence, drawing from state-of-the-art transformer modifications.
- Prototype and Scale: Rapidly prototype ideas and scale them to massive training runs for production deployment.
- Execute Experiments: Run autonomous and collaborative experiments, analyzing results to drive iterative improvements.
- Performance Debugging: Deep-dive into model performance issues, resolving regressions and enhancing capabilities.
- Computational Optimization: Optimize training and inference for peak efficiency on massive compute clusters.
- Infrastructure Contributions: Build and refine training/inference infrastructure to support frontier model development.
- Eval Framework Development: Create robust evaluation suites to benchmark architecture improvements objectively.
- Bottleneck Analysis: Systematically identify and eliminate computational bottlenecks in large-scale runs.
- Cross-Team Integration: Collaborate with research, product, and safety teams to deploy models safely.
- Long-Term Research: Pursue ambitious bets on next-generation architectures for AGI-scale systems.
- Model Artifact Production: Deliver world-class models like GPT-4-Turbo that power OpenAI products.
- Empirical Research: Apply hands-on, data-driven methods to validate and iterate on architectural hypotheses.
- Safety-Focused Deployment: Ensure architectures support safe, real-world LLM applications.
- State-of-the-Art Tracking: Stay ahead of transformer efficiency trends and integrate them rapidly.
These responsibilities position you as a pivotal player in OpenAI's mission to benefit humanity through safe AGI.
Qualifications
To excel as a Researcher, Training, you'll need proven expertise in LLM research. Top candidates demonstrate:
- Deep expertise in LLM architectures, including transformers and modifications for efficiency.
- Advanced understanding of model inference dynamics and optimization techniques.
- Track record of contributions to major LLM training runs (e.g., GPT-scale models).
- Self-directed ability to evaluate, improve, and deploy deep learning architectures.
- Empirical mindset: designing evals, debugging regressions, and optimizing baselines.
- Experience with PyTorch, JAX, or similar for large-scale model development.
- Knowledge of training infrastructure, distributed computing, and compute optimization.
- PhD/MS in ML, AI, CS, or equivalent with 5+ years research experience.
- Passion for safe AI deployment and real-world impact.
- Versatility in creative innovation and rigorous engineering.
- Strong collaboration skills in hybrid, fast-paced environments.
OpenAI values diverse perspectives and is committed to equal opportunity employment.
Salary & Benefits
Salary Range: $320,000 - $550,000 USD yearly (base + equity), commensurate with experience. Total compensation includes significant equity in OpenAI.
Comprehensive Benefits:
- Top-tier medical, dental, vision insurance.
- 401(k) with company match.
- Unlimited PTO and flexible hybrid schedule.
- Relocation package for SF move.
- Parental leave, wellness stipends, and gym access.
- Catered meals and mental health support.
- Professional growth funding and visa assistance.
Why Join OpenAI?
OpenAI is the leader in safe AGI development, powering innovations that transform industries. Work on frontier models with global impact, surrounded by top talent in San Francisco's vibrant tech hub. Our culture emphasizes safety, diversity, and humanity-first AI. Background checks align with fair chance laws.
How to Apply
Submit your resume, portfolio of LLM contributions, and a cover letter highlighting architecture innovations. OpenAI recruiters review applications promptly. Join us in building AGI for all!
Locations
- San Francisco, California, United States
Salary
336,000 - 605,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Large Language Models (LLMs)intermediate
- Transformer Architecturesintermediate
- Model Inference Optimizationintermediate
- Deep Learning Researchintermediate
- Neural Network Designintermediate
- Experiment Design and Analysisintermediate
- PyTorch Proficiencyintermediate
- Model Training Infrastructureintermediate
- Computational Performance Tuningintermediate
- Eval Design for AI Modelsintermediate
- Scaling AI Architecturesintermediate
- Bottleneck Debuggingintermediate
- State-of-the-Art Transformer Modificationsintermediate
- AGI Researchintermediate
- Empirical ML Researchintermediate
- Inference Efficiencyintermediate
- Model Prototypingintermediate
- Performance Regression Analysisintermediate
Required Qualifications
- Deep understanding of LLM architectures and transformer models (experience)
- Sophisticated knowledge of model inference processes and optimization (experience)
- Hands-on experience landing contributions to major LLM training runs like GPT-4 (experience)
- Proven ability to thoroughly evaluate and improve deep learning architectures independently (experience)
- Strong empirical approach to research, including experiment execution and analysis (experience)
- Experience designing evals, debugging regressions, and tracking performance bottlenecks (experience)
- Well-versed in state-of-the-art transformer modifications for efficiency and capability (experience)
- Motivation to safely deploy LLMs in real-world applications (experience)
- PhD or equivalent experience in machine learning, AI, or related fields preferred (experience)
- Track record of creative breakthroughs in model architecture development (experience)
- Familiarity with training and inference infrastructure at scale (experience)
- Ability to work autonomously and collaboratively in a fast-paced research environment (experience)
Responsibilities
- Design novel architectures to enhance model intelligence and capabilities
- Prototype experimental architectures and scale them to production levels
- Execute complex experiments autonomously and analyze results rigorously
- Collaborate with cross-functional teams on model development initiatives
- Study and debug model performance issues in depth
- Optimize computational performance for training and inference efficiency
- Contribute to the development of training infrastructure tools and pipelines
- Enhance inference infrastructure for faster and more efficient model deployment
- Develop comprehensive evaluation frameworks for new architectures
- Investigate and resolve thorny performance regressions in models
- Track down and eliminate computational bottlenecks in large-scale training
- Integrate long-term research bets into flagship model production
- Produce world-class model artifacts used across OpenAI products
- Push the frontier of AI capabilities toward AGI development goals
Benefits
- general: Competitive salary with equity in a high-growth AI company
- general: Comprehensive health, dental, and vision insurance coverage
- general: 401(k) retirement plan with generous company matching
- general: Relocation assistance for new employees moving to San Francisco
- general: Hybrid work model with 3 days in-office and flexibility
- general: Unlimited PTO policy to support work-life balance
- general: Generous parental leave and family planning benefits
- general: Professional development stipend for conferences and courses
- general: Onsite fitness facilities and wellness programs
- general: Catered meals, snacks, and beverages daily
- general: Mental health support through employee assistance programs
- general: Visa sponsorship for international talent
- general: Cutting-edge research environment with top talent
- general: Impactful work contributing to AGI and safe AI deployment
Tags & Categories
Answer 10 quick questions to check your fit for Researcher, Training Careers at OpenAI - San Francisco, California | Apply Now! @ OpenAI.
Related Books and Jobs
Researcher, Training Careers at OpenAI - San Francisco, California | Apply Now!
OpenAI
Researcher, Training Careers at OpenAI - San Francisco, California | Apply Now!
Job Description
Researcher, Training Careers at OpenAI - San Francisco, California | Apply Now!
Role Overview
Join OpenAI's elite Training team as a Researcher, Training in San Francisco, California, and become a key architect behind the world's most advanced large language models (LLMs). This senior-level role places you at the forefront of AI innovation, where you'll design, prototype, and scale groundbreaking architectures that power flagship models like GPT-4o, o1-mini, and future AGI systems. OpenAI's Training team is the powerhouse producing LLMs that drive research, products, and humanity's progress toward artificial general intelligence (AGI).
In this high-impact position, you'll combine deep research into architectures, datasets, and optimization with bold long-term bets on model efficiency and capabilities. Expect to integrate cutting-edge techniques into production model artifacts used company-wide. Ideal for researchers with hands-on experience in LLM development, this hybrid role (3 days/week in-office) offers relocation support and the chance to work alongside the brightest minds in AI.
The role demands a sophisticated grasp of model inference, empirical rigor, and versatility—from creative breakthroughs to baseline strengthening, eval design, regression debugging, and bottleneck hunting. If you're passionate about safely deploying world-class LLMs, this is your opportunity to shape the future of AI at OpenAI.
Key Responsibilities
As a Researcher, Training at OpenAI, your contributions will directly elevate model intelligence, efficiency, and new capabilities. Here's what you'll tackle daily:
- Design Novel Architectures: Innovate new model architectures to boost intelligence, drawing from state-of-the-art transformer modifications.
- Prototype and Scale: Rapidly prototype ideas and scale them to massive training runs for production deployment.
- Execute Experiments: Run autonomous and collaborative experiments, analyzing results to drive iterative improvements.
- Performance Debugging: Deep-dive into model performance issues, resolving regressions and enhancing capabilities.
- Computational Optimization: Optimize training and inference for peak efficiency on massive compute clusters.
- Infrastructure Contributions: Build and refine training/inference infrastructure to support frontier model development.
- Eval Framework Development: Create robust evaluation suites to benchmark architecture improvements objectively.
- Bottleneck Analysis: Systematically identify and eliminate computational bottlenecks in large-scale runs.
- Cross-Team Integration: Collaborate with research, product, and safety teams to deploy models safely.
- Long-Term Research: Pursue ambitious bets on next-generation architectures for AGI-scale systems.
- Model Artifact Production: Deliver world-class models like GPT-4-Turbo that power OpenAI products.
- Empirical Research: Apply hands-on, data-driven methods to validate and iterate on architectural hypotheses.
- Safety-Focused Deployment: Ensure architectures support safe, real-world LLM applications.
- State-of-the-Art Tracking: Stay ahead of transformer efficiency trends and integrate them rapidly.
These responsibilities position you as a pivotal player in OpenAI's mission to benefit humanity through safe AGI.
Qualifications
To excel as a Researcher, Training, you'll need proven expertise in LLM research. Top candidates demonstrate:
- Deep expertise in LLM architectures, including transformers and modifications for efficiency.
- Advanced understanding of model inference dynamics and optimization techniques.
- Track record of contributions to major LLM training runs (e.g., GPT-scale models).
- Self-directed ability to evaluate, improve, and deploy deep learning architectures.
- Empirical mindset: designing evals, debugging regressions, and optimizing baselines.
- Experience with PyTorch, JAX, or similar for large-scale model development.
- Knowledge of training infrastructure, distributed computing, and compute optimization.
- PhD/MS in ML, AI, CS, or equivalent with 5+ years research experience.
- Passion for safe AI deployment and real-world impact.
- Versatility in creative innovation and rigorous engineering.
- Strong collaboration skills in hybrid, fast-paced environments.
OpenAI values diverse perspectives and is committed to equal opportunity employment.
Salary & Benefits
Salary Range: $320,000 - $550,000 USD yearly (base + equity), commensurate with experience. Total compensation includes significant equity in OpenAI.
Comprehensive Benefits:
- Top-tier medical, dental, vision insurance.
- 401(k) with company match.
- Unlimited PTO and flexible hybrid schedule.
- Relocation package for SF move.
- Parental leave, wellness stipends, and gym access.
- Catered meals and mental health support.
- Professional growth funding and visa assistance.
Why Join OpenAI?
OpenAI is the leader in safe AGI development, powering innovations that transform industries. Work on frontier models with global impact, surrounded by top talent in San Francisco's vibrant tech hub. Our culture emphasizes safety, diversity, and humanity-first AI. Background checks align with fair chance laws.
How to Apply
Submit your resume, portfolio of LLM contributions, and a cover letter highlighting architecture innovations. OpenAI recruiters review applications promptly. Join us in building AGI for all!
Locations
- San Francisco, California, United States
Salary
336,000 - 605,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Large Language Models (LLMs)intermediate
- Transformer Architecturesintermediate
- Model Inference Optimizationintermediate
- Deep Learning Researchintermediate
- Neural Network Designintermediate
- Experiment Design and Analysisintermediate
- PyTorch Proficiencyintermediate
- Model Training Infrastructureintermediate
- Computational Performance Tuningintermediate
- Eval Design for AI Modelsintermediate
- Scaling AI Architecturesintermediate
- Bottleneck Debuggingintermediate
- State-of-the-Art Transformer Modificationsintermediate
- AGI Researchintermediate
- Empirical ML Researchintermediate
- Inference Efficiencyintermediate
- Model Prototypingintermediate
- Performance Regression Analysisintermediate
Required Qualifications
- Deep understanding of LLM architectures and transformer models (experience)
- Sophisticated knowledge of model inference processes and optimization (experience)
- Hands-on experience landing contributions to major LLM training runs like GPT-4 (experience)
- Proven ability to thoroughly evaluate and improve deep learning architectures independently (experience)
- Strong empirical approach to research, including experiment execution and analysis (experience)
- Experience designing evals, debugging regressions, and tracking performance bottlenecks (experience)
- Well-versed in state-of-the-art transformer modifications for efficiency and capability (experience)
- Motivation to safely deploy LLMs in real-world applications (experience)
- PhD or equivalent experience in machine learning, AI, or related fields preferred (experience)
- Track record of creative breakthroughs in model architecture development (experience)
- Familiarity with training and inference infrastructure at scale (experience)
- Ability to work autonomously and collaboratively in a fast-paced research environment (experience)
Responsibilities
- Design novel architectures to enhance model intelligence and capabilities
- Prototype experimental architectures and scale them to production levels
- Execute complex experiments autonomously and analyze results rigorously
- Collaborate with cross-functional teams on model development initiatives
- Study and debug model performance issues in depth
- Optimize computational performance for training and inference efficiency
- Contribute to the development of training infrastructure tools and pipelines
- Enhance inference infrastructure for faster and more efficient model deployment
- Develop comprehensive evaluation frameworks for new architectures
- Investigate and resolve thorny performance regressions in models
- Track down and eliminate computational bottlenecks in large-scale training
- Integrate long-term research bets into flagship model production
- Produce world-class model artifacts used across OpenAI products
- Push the frontier of AI capabilities toward AGI development goals
Benefits
- general: Competitive salary with equity in a high-growth AI company
- general: Comprehensive health, dental, and vision insurance coverage
- general: 401(k) retirement plan with generous company matching
- general: Relocation assistance for new employees moving to San Francisco
- general: Hybrid work model with 3 days in-office and flexibility
- general: Unlimited PTO policy to support work-life balance
- general: Generous parental leave and family planning benefits
- general: Professional development stipend for conferences and courses
- general: Onsite fitness facilities and wellness programs
- general: Catered meals, snacks, and beverages daily
- general: Mental health support through employee assistance programs
- general: Visa sponsorship for international talent
- general: Cutting-edge research environment with top talent
- general: Impactful work contributing to AGI and safe AI deployment
Tags & Categories
Answer 10 quick questions to check your fit for Researcher, Training Careers at OpenAI - San Francisco, California | Apply Now! @ OpenAI.
Related Books and Jobs