Trajectory’s mission to build the platform for continual learning is ambitious, and requires exceptional talent to make it happen. We hiring a Recruiter to design the operating system for how we find outliers, assess their fit for Trajectory, and convince them to join.
The best talent requires concerted time and effort throughout the recruiting process. We need someone who takes a first-principles, engineering mindset to talent to make the unscalable scalable, and creates new ways to hire exceptional people at speed, and is personally the person they meet.
Design how we identify exceptional people, assess their fit, and attract them to Trajectory.
Design an efficient interview pipeline that can go from first intro to offer in the shortest possible time
Build the systems that keep someone in Trajectory’s orbit (socials, coffee chats, intros) and encode scalable context so we can tailor our process to best fit what candidates our looking for
Run hand-sourcing as an always-on motion: talent mapping against target companies and labs, referral asks from every new hire and investor.
Go where the best people are and aren't looking for a job — open source, papers, conferences, competition circuits, campus hubs, X and GitHub follow graphs.
Build a personalized closing plan for every candidate we want, grounded in their motivations, blockers, timeline, and mutuals.
Work directly with the founders to go the unscalable last mile for every candidate, from the beginning of the process all the way to closing
You are a systems thinker who turns ambiguous processes into clear decisions, processes, execution, and automation.
You go the last mile. Finding and closing talent means hosting tailored events, identifying thoughtful gifts for candidates, and breaking process to move the needle.
You have taste for talent in technical and unusual roles. You can tell a polished, recruiter-shaped candidate from someone who will actually do the work.
You are an excellent communicator. You build trust quickly, convey context clearly, and adapt your message to candidates, founders, and teammates without losing precision.
You are metrics-driven. You define the measures that matter across the recruiting funnel, inspect conversion, speed, and quality, and use the data to decide what to improve next.
You are AI-pilled. Claude Code to build out dashboards and automations. Grok Bot to streamline comms and outreach. Any process you do twice can be systemized with AI.
You are highly proactive and low ego.
Trajectory is a research and product lab creating the platform for continual learning.
AI is the most capable software ever built, and the least able to learn. Trajectory unlocks the signal already sitting in product use so companies can continuously post-train large-scale agentic models that outperform the frontier. Working with leading AI companies, including Decagon, Clay, Harvey, Mercor, and Rogo.
Founded by researchers from DeepMind, OpenAI, Meta, Apple, Amazon, and Scale. Raised $60M from Sequoia, Conviction, along with Fei-Fei Li, Jeff Dean, and founders of Notion, Braintrust, Modal, Hugging Face, and Dropbox.
Skills Required
- Systems thinker who can turn ambiguous processes into clear decisions, processes, execution, and automation
- Ability to take initiative and go the last mile for candidates
- Strong judgment for identifying exceptional talent, especially for technical and unusual roles
- Excellent communication and relationship-building skills
- Metrics-driven approach to recruiting funnel conversion, speed, and quality
- Ability to use AI tools to build dashboards, automations, and streamline communications
- Highly proactive and low-ego working style
What We Do
Trajectory is a research and product lab building a platform for continual learning. Its infrastructure captures product-usage signals such as traces, corrections, re-prompts, and edits, then helps teams understand model behavior, steer optimization, and continuously post-train and deploy improved AI systems. The company works with AI organizations across customer service, go-to-market, and legal applications, bringing production feedback into the learning loop.
