OpenAI
AI Research and Deployment
Researcher,Connectors-AgentPost-Training
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Researcher, Connectors - Agent Post-Training at OpenAI. Skills: Agent Post-Training, LLMs, RL. Design and run experiments. improve agentic model behavior”
What You'll Achieve.
improve agentic model behavior; ship improvements into products; make agents genuinely useful
Industry & Context.
open-ended problems; vague behavioral problem to a concrete experiment; define the hypothesis; build the pipeline; run the model; analyze the result; decide what to do next; messy qualitative behavior into concrete hypotheses
What They're Looking For.
Must Have
technical fundamentals in machine learning, software engineering, systems, statistics, hands-on experience with LLMs, RL, RLHF/RLAIF, post-training, evals, graders, synthetic data, model training, coding agents, tool-using agents, production ML systems
Nice to Have
experience with Python and machine learning frameworks, experience with Slack, experience with Google Workspace, experience with GitHub, experience with Notion, experience with Linear, experience with Salesforce
What You'll Do.
Design and run experiments
improve agentic model behavior
Own end-to-end improvements
Build evals and environments
expose model failures
Partner with product teams
translate product signal
Work on training and alignment interventions
Help decide integrations
Improve machinery for training
Take on cross-functional projects
turn qualitative behavior into hypotheses
How You'll Work.
Team & Collaboration
Partner with researchers; engineers; product teams; infrastructure teams; safety/alignment partners; Work across research; product; infrastructure; data; evals; safety boundaries
Communication Scope
communicate clearly with each group
Full Job Description
About the Team The Agent Post-Training team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve. We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste. Our team is where new model capabilities get made. We build the data, environments, graders, training methods, and feedback loops that shape what OpenAI's next agents can do, then carry those capabilities through major training runs and into the products people use. About the Role As a member of Agent Post-Training, Connectors, you will teach models how to interface with the top professional software using code. You will help train agents to use code, APIs, tools, and structured integrations to operate across applications like Slack, Google Workspace, GitHub, Notion, Linear, Salesforce, and other core systems of work. You will help enable models to take useful actions across a user’s digital context: finding information, updating systems, coordinating work, generating artifacts, and completing multi-step workflows through the tools teams already use. You will train models to be supercharged by the world’s most important productivity and enterprise software, turning connected tools into a powerful action surface for our agents. You will work with researchers, engineers, product teams, infrastructure teams, and safety/alignment partners to decide what should go into major model runs, measure whether it worked, and ship improvements into products used by real people.
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