Join a cutting-edge AI research environment to help define how frontier language models are evaluated and benchmarked. Design and develop original evaluation methodologies, develop high-quality benchmarks, and collaborate with subject matter experts. Ideal for a researcher who enjoys solving complex methodological challenges and contributing to the advancement of trustworthy AI evaluation.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Job Description
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Research Scientist based in Brazil.
Join a cutting-edge AI research environment where you will help define how frontier language models are evaluated and benchmarked. In this highly technical role, you will design rigorous evaluation methodologies, develop high-quality benchmarks, and collaborate with subject matter experts to assess advanced capabilities across reasoning, coding, multimodal systems, and agentic AI. You will play a key role in ensuring evaluation frameworks are scientifically robust, reproducible, and aligned with the evolving needs of leading AI research organizations. This opportunity is ideal for a researcher who enjoys solving complex methodological challenges and contributing to the advancement of trustworthy AI evaluation.
Accountabilities
- Design and develop original evaluation methodologies that accurately measure the capabilities of frontier AI models across reasoning, coding, agentic workflows, tool use, and multimodal tasks.
- Create comprehensive benchmark packages supported by expert-verified ground truth, rigorous quality control processes, deterministic verification methods, and well-calibrated scoring rubrics.
- Evaluate benchmark quality by ensuring strong construct validity, appropriate task discrimination, sufficient performance headroom, and minimal benchmark contamination.
- Recruit, assess, and coordinate subject matter experts to develop, validate, and review high-quality evaluation datasets and benchmark content.
- Serve as the final technical reviewer for evaluation quality, benchmark correctness, and task complexity before external delivery.
- Collaborate with AI research organizations to understand evaluation objectives and translate research needs into effective benchmarking strategies.
- Lead evaluation pilots from initial concept through final delivery, ensuring all outputs meet demanding scientific and technical standards.
- Continuously refine evaluation methodologies to support emerging capabilities and evolving best practices in frontier AI research.
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- Demonstrated research experience in machine learning evaluation, benchmarking, AI assessment methodologies, or a closely related field.
- Proven expertise designing or contributing to AI benchmarks, evaluation research, published datasets, or similar research initiatives relied upon by AI organizations.
- Strong understanding of large language model evaluation, including benchmarking methodologies, scoring rubrics, pass rates, contamination risks, construct validity, and discriminative task design.
- Deep knowledge of code model evaluation and technical assessment frameworks for advanced AI systems.
- Experience working with subject matter experts and maintaining rigorous quality standards across technical research projects.
- Excellent analytical, research, and problem-solving skills with a strong attention to scientific rigor.
- Outstanding written and verbal communication skills in English.
- Ability to work independently in a remote, research-driven environment while collaborating effectively with multidisciplinary teams.
- Spanish language proficiency is considered a plus.
- Fully remote contract position based in Brazil.
- Opportunity to work on frontier AI research and evaluation projects with global impact.
- High level of ownership and influence over research methodology and benchmark design.
- Collaboration with leading AI experts, researchers, and technical specialists.
- Flexible remote working environment that supports autonomy and innovation.
- Exposure to cutting-edge advancements in large language models and AI evaluation.
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