TL;DR
Member Of Technical Staff (AI): Designing, building, and owning the entire lifecycle of intelligent computer-use agents capable of surpassing human performance, with an accent on multimodal foundation models and robust infrastructure for scalable data pipelines. Focus on crafting data recipes, applying RL techniques for generalization, and iterating on high-quality evaluations.
Location: Palo Alto, CA. Final interviews are conducted in person.
Salary: $180,000–$440,000 USD
Company
hirify.global’s mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge.
What you will do
- Design and build architectures for intelligent computer-use agents.
- Collect, curate, and craft high-quality multimodal interaction data and recipes for training.
- Pre-train, fine-tune, and apply Reinforcement Learning (RL) techniques to foundation models.
- Develop robust infrastructure for scalable data pipelines, distributed training, and evaluation.
- Deploy, monitor, and continuously improve the agent lifecycle flywheel.
Requirements
- Exceptional engineers who own work end-to-end and thrive in meritocratic environments.
- Strong commitment to quality, rigor, and first-principles thinking.
- Strong communication skills for knowledge sharing.
- Deep expertise in multimodal foundation models or crafting pre-training/mid-training data recipes.
- Experience building robust infrastructure and frameworks for the agent lifecycle.
- Experience applying RL techniques to complex, long-horizon computer-use tasks.
- English: B2 required
Culture & Benefits
- Small, highly motivated team focused on engineering excellence.
- Flat organizational structure where all employees are hands-on.
- Leadership based on initiative and consistent delivery.
- Emphasis on work ethic and strong prioritization skills.
- Comprehensive medical, vision, and dental coverage.
- Access to a 401(k) retirement plan.
- Short & long-term disability insurance and life insurance.
Hiring process
- CV and statement of exceptional work review.
- 15-minute call with a team member.
- 3 technical onsite interviews.
- 1 meet-the-team interview to present exceptional work.
- Process aims to finish within one week.
- Final interviews conducted in person.
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