About Us:

The AI platform for human intelligence—we build models that rigorously vet PhDs and scale human data training for frontier LLMs.

Our agent, Zara, autonomously sources and evaluates world-class researchers and data trainers—powering post-training (RLHF, evals, red-teaming) for top AI labs, modernizing staffing firms, and helping startups hire their core AI teams.

Long term, we’re the default engine behind expert talent—creating the highest-quality, pre-vetted global pool on earth.

Job Summary

Join our engineering team and help shape the future of recruiting technology—already trusted by almost every major AI Lab. You’ll work hands-on with Zara, our pioneering AI Recruiter model, to design, build, and scale next-generation systems that are redefining how companies identify and engage talent, while collaborating across disciplines to deliver cutting-edge solutions at the center of the AI revolution.

What You'll Do

• Architect and Develop Systems: Design, build, and deploy scalable AI models and infrastructure leveraging Python and AWS.
• Advance Multimodal AI: Develop and integrate advanced LLMs and multimodal systems (text, audio, video, and visual inputs) into core platforms.
• Collaborate Cross-Functionally: Partner with product, research, and engineering teams to translate requirements into robust technical solutions.
• API Frameworks: Build efficient APIs using LangChain and FastAPI to enhance system performance and interoperability.
• Research & Innovation: Stay at the forefront of AI advancements and drive adoption of cutting-edge multimodal AI technologies.

What We're Looking For

• Bachelor’s degree in Computer Science, Engineering, or related technical field.
• Proven experience in Python programming and building systems in AWS environments.
• Strong hands-on experience with LLMs, LangChain, and multimodal AI frameworks.
• Proficiency in developing APIs (FastAPI, Flask, or similar).
• Strong problem-solving skills with the ability to operate independently.
• Excellent communication skills, both written and verbal.

Preferred Qualifications

• Master’s degree or higher in a relevant technical field.
• Experience in technical leadership, mentoring, or guiding engineering teams.
• Contributions to open-source AI projects or published research.
• Familiarity with GPU programming and optimization for deep learning workloads.