Member of Technical Staff, Frontier AI | $100-$130/hr Remote
Overview
We’re looking for a Member of Technical Staff to own the bridge between research, data, and production AI systems. In this hands-on role, you’ll drive model and system improvements through rigorous evaluation, failure analysis, and fast iteration. You’ll collaborate with researchers and domain experts to turn experimental insights into measurable, real-world performance gains.
What You'll Do6
- 1Take end-to-end ownership of research and evaluation initiatives — from framing the problem and designing data pipelines to calibrating quality and validating results.
- 2Build ML-oriented data systems that include task definitions, annotation schemas, rubrics, and incentive structures, all optimized to boost downstream model performance.
- 3Analyze model and system failures to pinpoint root causes, uncover edge cases, and identify high-impact improvements.
- 4Translate messy, real-world behavior into structured evaluation frameworks and new data categories that drive clearer research signals.
- 5Act as a quality gate — blocking premature claims, pausing work, or forcing scope changes when data integrity or signal strength isn’t sufficient.
- 6Work cross-functionally with client-facing teams to turn research progress into compelling, evidence-backed narratives.
Requirements6
- 1Strong judgment about research signal quality — you know when work is (and isn’t) ready to go public.
- 2Hands-on experience designing ML datasets, evaluation frameworks, and QA processes that improve model performance.
- 3Comfort navigating ambiguity with a bias toward ownership and decisive action, even when the path isn’t clear.
- 4Clear written and verbal communication — you can explain tradeoffs, limitations, and signal strength to both technical and non-technical stakeholders.
- 5Preferred: experience with reinforcement learning environments, simulators, or feedback-driven training systems.
- 6Preferred: background in improving agentic systems or AI systems that operate in real-world workflows.
Who Should Apply
This role is ideal for someone who thrives at the intersection of research engineering and production AI. You’re the person who can take a vague problem, structure it into a rigorous evaluation, and drive execution until the system actually improves. You’re comfortable owning outcomes, pushing back when data isn’t strong enough, and communicating complex ideas clearly. If you have experience with reinforcement learning, agentic systems, or applied research, you’ll fit right in.
Salary Insight
Base salary ranges from $180,000 to $320,000, plus equity compensation and performance-based bonuses. The company also offers comprehensive benefits including up to 100% reimbursement for health-insurance premiums, paid time off, and a 401(k) plan with company match.
Required Skills
Application Tip
When applying, include a brief write-up or example of a time you identified a weakness in a model evaluation framework and successfully improved it — this role values concrete evidence of your judgment and signal-building skills.
Similar open positions
Explore active roles that match your skills and interests.
Micro1
VerifiedMember of Technical Staff, Enterprise AI | $100-$130/hr Remote
This role is for a hands-on research partner who embeds directly within enterprise AI systems to uncover real-world issues and drive rapid improvements. You'll work on live workflows, identify failure patterns, and run tight experimental cycles to boost system performance. It's a unique blend of applied research and engineering, aimed at making AI more robust in production environments. If you thrive in ambiguous, fast-paced settings and love turning operational problems into structured research questions, this could be your next move.
Micro1
VerifiedMember of Technical Staff, Research Engineering | $7-$8/hr Remote
This role places you at the cutting edge of Reinforcement Learning, where you'll build novel training environments, scalable pipelines, and robust evaluation frameworks that push the boundaries of AI. You'll bridge the gap between research and production, turning experimental concepts into high-performance systems that power real-world applications. As a key member of the research engineering team, you'll own the full lifecycle of RL system development, from environment design to model fine-tuning.
Micro1
VerifiedMember of Technical Staff, Finance Research | $6-$8/hr Remote
This role sits at the cutting edge where artificial intelligence meets finance. As a Member of Technical Staff on the Finance Research team, you'll design and own the evaluation frameworks that measure how well AI systems handle complex financial tasks—from reasoning and decision-making to full workflow automation. You'll work closely with researchers and engineers to push the boundaries of what AI can do in enterprise finance, turning cutting-edge research into tangible improvements.
Micro1
VerifiedForward Deployed Engineer | $300K - $650K/yr | Remote
This role sits at the intersection of applied AI, ML infrastructure, and partner-facing product development. You'll work directly with leading AI labs and enterprises to transform ambiguous research questions into production-grade systems. As a Member of Technical Staff, you'll own everything from data curation and LLM agent workflows to deployment and partner success — all while operating in a fast-moving, remote-first environment.
Micro1
VerifiedMember of Technical Staff, Forward Deployed (US Gov) | $40-$60/hr Remote
This role places you at the intersection of cutting-edge AI and critical U.S. Government missions. As a Member of Technical Staff, you’ll design, build, and deploy agentic AI systems that move from prototype to production in high-assurance environments. You’ll work closely with government partners, owning the full lifecycle of systems that turn mission data into operational autonomy.
Micro1
VerifiedMember of Technical Staff, Coding Research | $8-$9/hr Remote
This role sits at the intersection of AI research, software engineering, and model evaluation. You'll design the benchmarks, methodologies, and data systems that define how next-generation coding models are measured and improved. It's a chance to directly shape the capabilities of frontier coding agents in a remote-first, research-driven environment.