Job Description

Job Title: Member of Technical Staff, Frontier AI

Job Type: Full time

Location: Remote

The Role

We’re hiring a Member of Technical Staff (MTS) to act as a technical owner operating at the intersection of research, data, and real-world AI systems. This is a hands-on role focused on improving model and system performance through rigorous evaluation, failure analysis, and iterative development.

You’ll work closely with researchers, domain experts, and operators to ensure that experimental work produces clean, defensible research signal—and that this signal translates into meaningful improvements in deployed systems.

What You’ll Do

Own research and evaluation initiatives end-to-end: problem framing, data design, quality calibration, and signal validation.
Design ML-oriented data systems, including task definitions, annotation schemas, rubrics, incentives, and pipelines optimized for downstream model performance.
Analyze model and system failures to identify root causes, edge cases, and opportunities for improvement.
Translate ambiguous, real-world behavior into structured evaluation frameworks and new data categories.
Work closely with researchers and domain experts to calibrate quality early and continuously raise the signal bar.
Iterate rapidly on evaluations, datasets, and feedback loops to improve system performance.
Act as a quality gate: block claims, pause work, or force scope changes when signal strength or data integrity is insufficient.
Partner with cross-functional and client-facing teams to translate research progress into clear, credible narratives grounded in evidence.
Identify gaps in data or evaluation coverage and recommend where to invest, iterate, or stop based on learnings and impact.

What We’re Looking For

Strong judgment around research signal quality and when work is (or is not) ready to be externalized.
Experience designing ML-oriented datasets, evaluation frameworks, and QA processes.
Ability to translate messy, real-world system behavior into structured research and evaluation opportunities.
Comfort operating in ambiguity, with a bias toward ownership and decisive action.
Clear written and verbal communication, especially when explaining tradeoffs, limitations, and signal strength to technical and non-technical stakeholders.
Proven ability to work directly with experts during project kickoff, calibration, and iteration.
A systems-level mindset, with interest in improving end-to-end model or agent performance rather than isolated components.

Preferred

Experience with reinforcement learning environments, simulators, or feedback-driven training systems.
Experience improving agentic systems or AI systems operating in real-world workflows.
Prior work embedded in applied research or production environments with direct impact on deployed systems.
Experience with evaluation design for complex or real-world tasks.
Familiarity with expert incentive design and engagement in high-stakes technical projects.

Compensation & Benefits Notice

The national pay range for this full-time position is base salary of $180,000 –$320,000. All employees are eligible for equity compensation, and employees may also receive performance-based bonuses, dependent on role and subject to company policies. micro1 provides a comprehensive benefits package, including up to 100% reimbursement for health-insurance premiums, paid time off, a 401(K) plan with a company match, and additional benefits designed to support a high-performing, remote-first workforce.

micro1 is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, veteran status, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation during the application process, reach out to support@micro1.ai.

Our hiring process utilizes artificial intelligence tools to assist in candidate screening and assessment. Our AI tools are designed to complement, not replace, human decision-making.

Disclaimer

The information contained in this job posting, including but not limited to role responsibilities, qualifications, compensation, and benefits, is provided for informational purposes only and does not constitute a binding offer of employment. micro1 reserves the right to amend, modify, or withdraw any portion of this posting at its sole discretion and without prior notice. All employment decisions are made in accordance with applicable laws and regulations.

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About Micro1

Micro1 is building the essential infrastructure for the next generation of artificial intelligence, moving beyond the limitations of static datasets to create a dynamic ecosystem where models truly learn to think and act. At its core, the company understands that the path to frontier intelligence isn't paved with synthetic data alone; it requires the nuance, judgment, and contextual awareness that only expert human guidance can provide. By positioning itself at the intersection of human expertise and advanced reinforcement learning, Micro1 is tackling the hardest problem in AI today: teaching models not just to answer questions, but to reason through complexity and take meaningful actions in unpredictable, real-world environments.

This mission comes to life through Realm, Micro1's flagship training environment. Realm functions as a high-fidelity simulation ground where AI agents are immersed in scenarios that closely mirror the messiness of actual human workflows. Rather than relying on abstract benchmarks, Realm forces models to engage in agentic actions, multi-step decisions, digital navigation, coding, and problem-solving that require genuine comprehension. It is within these realistic sandboxes that world-class human data is generated, creating a continuous feedback loop where expert annotators observe, correct, and guide model behavior. This process does more than just fine-tune outputs; it fundamentally elevates a model's underlying reasoning architecture, ensuring that the intelligence developed in training holds up when deployed into the wild.

But training is only half the equation. Micro1 recognizes that the true test of an AI system lies in its production performance, which is where Cortex enters the picture. Cortex is a contextual evaluation platform designed to move beyond superficial accuracy metrics and provide a granular, real-time view of how agents behave in live settings. It doesn't just flag errors; it surfaces the underlying context behind failures, revealing why an agent struggled with a particular user intent or environmental variable. This insight is invaluable for engineering teams, as it transforms evaluation from a passive checkpoint into an active improvement tool. With Cortex, companies can catch degradation early, understand the nuances of edge cases, and feed those learnings directly back into Realm for retraining, creating a virtuous cycle of continuous advancement.

Ultimately, Micro1 is not merely a data lab or an evaluation tool it is a comprehensive intelligence engine that connects the entire lifecycle of model development. From the expert human feedback that sharpens raw capability, to the realistic RL environments that forge robust agentic behavior, to the contextual oversight that ensures reliability in production, Micro1 provides the integrated foundation that AI labs and enterprises desperately need. As the industry races toward truly autonomous systems, Micro1 stands as the critical bridge between laboratory breakthroughs and dependable, real-world impact, ensuring that frontier models do not just perform well on paper, but deliver genuine value in the complex, dynamic world they are meant to serve.