Research Engineer, Benchmarks
Singapore · hoy
Diseñarás, implementarás y mantendrás benchmarks específicos por dominio para evaluar agentes de IA, y construirás infraestructura para ejecutar modelos y agentes sobre ellos a gran escala. También analizarás la fiabilidad y los modos de fallo de los benchmarks y redactarás informes técnicos sobre los resultados.
- Modalidad
- Presencial
- Nivel
- Intermedio
- Salario
- 100K USD/año - 170K USD/año
- Experiencia
- 2+ años
- Equipo
- Engineering
- Patrocinio de visado
- Disponible
Skills
Sobre el puesto
About the Role Join a small, technical team at an early-stage AI evaluation company building benchmarks for frontier AI agents. You will own the design and implementation of rigorous, domain-specific evaluations that help research teams and customers understand real-world agent performance. What You'll Do • Design, implement, and maintain benchmarks for evaluating AI agents on domain-specific tasks. • Work with subject-matter experts to translate real workflows into realistic tasks and evaluation criteria. • Build reliable infrastructure for running models and agents against benchmark tasks at scale. • Develop metrics and analyses to assess benchmark difficulty, reliability, and failure modes. • Validate how benchmark results relate to real-world evaluations and user needs. • Write clear technical documentation and reports communicating benchmark methods and results. What We're Looking For • Two to four years of experience in research engineering, machine learning engineering, or a related technical role, including at least two years building or delivering AI benchmarks, evaluation infrastructure, or agent environments. • Strong proficiency in Python, Docker, and Linux for research or production infrastructure. • Hands-on experience designing, implementing, and operating evaluations for AI agents or large language models. • Experience building infrastructure to run models or agents reliably, and developing metrics, statistical analyses, or validation studies. • Ability to collaborate with subject-matter experts and analyze workflows across different domains to create useful evaluation tasks. • Strong technical writing, attention to detail, first-principles reasoning, and comfort working independently in a fast-paced startup. • Published research or technical writing on benchmarking, model evaluation, or failure modes is valued. Reinforcement learning pipelines, data generation, and agent evaluation experience are also relevant. Compensation & Benefits Base salary: $100,000 to $170,000 USD annually. Visa sponsorship is available. Location On-site in Singapore, Singapore.
Publicada el 8 nov 2026
