Remote MTS: AI Research & Systems Engineer

RemoteJobsOne; Atlanta (GA); Remote; USD 600,000 - 2,000,000; Full time

Job summary

RemoteJobsOne is hiring a Member of Technical Staff (MTS) for Frontier AI, fully remote in the United States. You will own research and evaluation at the intersection of research, data, and real-world AI systems.

You will design ML-oriented data systems, analyze failures, and translate research progress into credible narratives for stakeholders. A strong emphasis on quality gates and end-to-end improvements is key.

Qualifications

• Design ML-oriented datasets, evaluation frameworks, and QA processes.
• Own end-to-end research and evaluation initiatives.
• Translate messy real-world behavior into structured evaluation.
• Collaborate with researchers and domain experts.
• Calibrate quality early and raise the signal strength.

Responsibilities

• 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.
• Analyze model and system failures to identify root causes and opportunities.
• Translate ambiguous behavior into structured evaluation frameworks and data categories.
• Work with researchers to calibrate quality and raise the signal bar.
• Iterate on evaluations, datasets, and feedback loops to improve system performance.
• Act as a quality gate: block claims, pause work, or force scope changes.
• Partner with cross-functional teams to translate research progress into credible narratives.
• Identify data/evaluation gaps and advise on investments or stops.

Skills

Research signal quality

Evaluation frameworks

QA processes

Ambiguity tolerance

Communication skills

Cross-functional teamwork

Job description

RemoteJobsOne is hiring a Member of Technical Staff (MTS) for Frontier AI, fully remote in the United States. You will own research and evaluation at the intersection of research, data, and real-world AI systems.

You will design ML-oriented data systems, analyze failures, and translate research progress into credible narratives for stakeholders. A strong emphasis on quality gates and end-to-end improvements is key.