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UU. busca un ingeniero de pruebas de IA/LLM meticuloso e innovador a tiempo completo para unirse a nuestro avanzado equipo de inteligencia artificial. En este rol fundamental, evaluará el rendimiento, la confiabilidad y la seguridad de los modelos de lenguaje grande (LLMs) en escenarios reales de productos y probará soluciones de inteligencia artificial generativa de extremo a extremo. Su trabajo moldeará directamente la experiencia del usuario con funciones impulsadas por IA, garantizando solidez, precisión y alineación con los objetivos del producto. Esta es una oportunidad única para liderar metodologías de prueba para sistemas de IA de próxima generación en la vanguardia tecnológica.\r\nTambién buscamos un ingeniero de evaluación y aseguramiento de calidad (QA) de LLM como contratista para apoyar las pruebas y validación de aplicaciones impulsadas por modelos de lenguaje grande (LLM). Ayudará a implementar estrategias de prueba, ejecutar flujos de trabajo de evaluación y asistir en la validación del rendimiento del modelo en diversos casos de uso de inteligencia artificial generativa.\r\nEste puesto de contrato es ideal para alguien con experiencia práctica en evaluación de IA/ML, ingeniería de QA o análisis de datos que desee profundizar su conocimiento en sistemas de inteligencia artificial generativa. \r\nRequisitos\r\nRequisitos para el puesto a tiempo completo:\r\n\r\nPruebas y evaluación principales\r\n Diseñar y ejecutar pruebas de rendimiento para LLMs en diversos casos de uso del producto (por ejemplo, chatbots, generación de contenido, etc.).\r\n Desarrollar marcos de pruebas automatizadas para evaluar las salidas de LLMs en cuanto a precisión, sesgo, seguridad y coherencia.\r\n Realizar pruebas de extremo a extremo de soluciones integradas de inteligencia artificial generativa, incluyendo APIs, canalizaciones de datos e interfaces de usuario.\r\n Optimización y validación\r\n Colaborar con ingenieros de ML para validar modelos ajustados y optimizar indicaciones (prompts) para escenarios específicos.\r\n Analizar fallos del modelo, casos límite y entradas adversarias para identificar riesgos y áreas de mejora.\r\n Comparar el rendimiento del LLM con estándares de la industria y KPIs específicos del producto.\r\n Colaboración y aseguramiento de calidad\r\n Colaborar con los equipos de producto, ingeniería e investigación para definir requisitos de prueba y criterios de aceptación.\r\n Documentar defectos, métricas de rendimiento y resultados de pruebas para impulsar mejoras basadas en datos.\r\n Promover la ética y seguridad de la IA mediante pruebas rigurosas de equidad, mitigación de sesgos y moderación de contenidos.\r\n Innovación y herramientas\r\n Crear herramientas escalables para la generación sintética de datos de prueba, pruebas de variación de indicaciones y flujos de trabajo de evaluación automatizados.\r\n Mantenerse actualizado con los avances en pruebas de inteligencia artificial generativa, incluyendo técnicas de red teaming y marcos de evaluación (por ejemplo, HELM, Dynabench).\r\n Proponer nuevas estrategias de prueba para desafíos emergentes (por ejemplo, alucinaciones, deriva de contexto).\r\n \r\nCualificaciones básicas:\r\n Título universitario en Ciencias de la Computación, Ciencia de Datos, Ingeniería o campo técnico relacionado, o experiencia práctica equivalente.\r\n 1 o más años de experiencia en pruebas de software, ciencia de datos o validación de ML, con exposición a sistemas de IA/ML.\r\n Dominio de Python y marcos de pruebas (por ejemplo, PyTest, Selenium).\r\n Experiencia práctica evaluando LLMs en entornos de producción (por ejemplo, GPT, Claude, Llama, Gemini).\r\n Sólidas habilidades analíticas para analizar el comportamiento del modelo, el rendimiento estadístico y los modos de fallo.\r\n Conocimiento de plataformas en la nube (GCP, Azure o AWS) y herramientas MLOps (por ejemplo, MLflow, Weights & Biases).\r\n Experiencia con control de versiones (Git) y metodologías de desarrollo ágiles.\r\n Cualificaciones preferidas:\r\n Maestría en IA, Aprendizaje Automático o campo relacionado.\r\n Experticia en ingeniería de indicaciones (prompt engineering), ajuste fino de LLMs (por ejemplo, LoRA, RLHF) o técnicas de optimización.\r\n Experiencia con herramientas de evaluación automatizada (por ejemplo, LangChain, TruLens) o conjuntos de pruebas específicos para LLM.\r\n Conocimiento de canalizaciones de datos, bases de datos SQL/NoSQL y pruebas de API (por ejemplo, Postman).\r\n Formación en estadística, análisis cuantitativo o visualización de datos para obtener conclusiones de pruebas.\r\n Participación en iniciativas de seguridad/ética de IA o proyectos de código abierto de evaluación de LLM.\r\n Experiencia en pruebas de soluciones de IA integradas en dispositivos móviles (Android/iOS).\r\n \r\nRequisitos para el puesto de contratista:\r\nSoporte en pruebas y evaluación:\r\n Ejecutar pruebas de rendimiento predefinidas para LLMs en diversas tareas (por ejemplo, resúmenes, preguntas y respuestas, flujos de chatbot). \r\n Realizar evaluaciones guiadas para evaluar las salidas en cuanto a veracidad, coherencia y seguridad. \r\n Realizar pruebas manuales y automatizadas en APIs e interfaces de usuario integradas con LLM. \r\n Validación de indicaciones y modelos:\r\n Asistir a ingenieros de ML en la evaluación de variaciones de indicaciones y resultados de ajuste de indicaciones (prompt tuning). \r\n Registrar y analizar casos de fallo, anomalías y casos límite según las pautas proporcionadas. \r\n Colaboración y documentación\r\n Trabajar con líderes de QA, gerentes de producto e ingenieros de ML para comprender los objetivos y criterios de prueba. \r\n Informar defectos, compilar resúmenes de evaluación y mantener registros de pruebas. \r\n Herramientas y automatización:\r\n Utilizar herramientas o marcos internos existentes para automatizar ejecuciones de pruebas y recopilación de resultados. \r\n Contribuir a procesos de generación de indicaciones, plantillas de entrada o etiquetado de resultados.\r\n \r\nCualificaciones básicas:\r\n Título universitario o experiencia laboral equivalente en un campo técnico (por ejemplo, Ciencias de la Computación, Ingeniería, Ciencia de Datos). \r\n 6 o más meses de experiencia en QA de software, etiquetado de datos, evaluación de LLM o proyectos de pruebas de ML. \r\n Dominio básico de Python, especialmente para tareas de procesamiento de datos y automatización. \r\n Familiaridad con LLMs (por ejemplo, GPT, Claude, Gemini) y salidas basadas en indicaciones. \r\n Capacidad para trabajar con herramientas como Jupyter, Postman o paneles de pruebas. \r\n Persona detallista con buenos hábitos de documentación.\r\n \r\nDetalles del contratista:\r\n Duración: Largo plazo \r\n Tarifa: Proporcional a la experiencia \r\n Oportunidad de conversión: Los contratistas con alto desempeño podrán ser considerados para puestos a tiempo completo \r\n Beneficios\r\nOPPO se enorgullece de ser un lugar de trabajo con igualdad de oportunidades. Estamos comprometidos con la igualdad de oportunidades laborales independientemente de raza, color, ascendencia, religión, sexo, origen nacional, orientación sexual, edad, ciudadanía, estado civil, discapacidad, identidad de género o condición de veterano. También consideramos candidatos calificados independientemente de sus antecedentes penales, de acuerdo con los requisitos legales.\r\nEl rango salarial base en EE. UU. para este puesto a tiempo completo es de $100,000-$200,000 + bono + incentivos a largo plazo y beneficios. Nuestros rangos salariales se determinan por rol, nivel y ubicación.\r\n","price":"$100,000-200,000/año","unit":"per year","currency":null,"company":"Workable","language":"es","online":1,"infoType":1,"biz":"jobs","postDate":"1756713232000","seoName":"test-engineer-ai-llm","supplement":null,"author":null,"originalPrice":null,"soldCnt":null,"topSeller":null,"source":1,"cardType":null,"action":"https://us.ok.com/es/city-san-francisco/cate-product-mgmt-dev1/test-engineer-ai-llm-6339351061542712/","localIds":"11037","cateId":null,"tid":null,"logParams":{"tid":"289e9a87-f402-46a7-93e3-6b680b0f2e7a","sid":"81efbc94-8384-425c-aa33-d9bf2b9f1734"},"attrParams":{"summary":null,"highLight":["Evaluar el rendimiento de los modelos de lenguaje grande (LLM) en escenarios del mundo real","Desarrollar marcos de pruebas automatizadas para modelos de inteligencia artificial","Colaborar con ingenieros de aprendizaje automático en la validación de modelos"],"employment":[{"icon":"https://sgj1.ok.com/yongjia/bkimg/8hvituaa__w72_h72.webp","name":"Tipo de empleo","value":"Tiempo completo","unit":null},{"icon":"https://sgj1.ok.com/yongjia/bkimg/is8j0f44__w72_h72.webp","name":"Modalidad de trabajo","value":"Presencial","unit":null},{"icon":"https://sgj1.ok.com/yongjia/bkimg/ji66qqr0__w72_h72.webp","name":null,"value":"East Palo Alto,California","unit":null}]},"addDate":1755261801682,"categoryName":"Gestión y Desarrollo de Productos","postCode":null,"secondCateCode":"info-comm-technology","kycTag":null,"pictureUrls":null,"isFavorite":false},{"category":"4000,4241,4254","location":"Walnut Creek, CA, USA","infoId":"6349978322880312","pictureUrl":"https://uspic1.ok.com/post/image/fc2dfa4f-dccd-4b5b-b64c-e4037dc4d35f.jpg","videos":null,"title":"✅ Líder de Desarrollo de Producto ✅","content":"Resumen\r\n \r\nEstamos construyendo el J.A.R.V.I.S. del mundo real para la I+D de materiales (https://exabyte.io/img/iron-man-creates-material.gif).\r\n\r\nBuscamos gerentes de producto con experiencia: personas con sólidos antecedentes técnicos (título STEM, experiencia en industrias similares) interesadas en diseñar y construir una plataforma integral basada en web (piense en AutoDesk, SAP, Adobe Creative Cloud, Azure ML Studio) para la I+D digital de materiales.\r\nEl trabajo se centrará en (1) identificar vías estratégicas para el desarrollo de productos, (2) preparar formas de obtener y recopilar comentarios de usuarios, y (3) redactar e implementar las funciones del producto. Los candidatos exitosos continuarán en roles de liderazgo a medida que crezcamos.\r\nEsta es una posición permanente a tiempo completo.\r\n \r\nResponsabilidades\r\n planificación y organización del trabajo de desarrollo de productos\r\n comunicación con los usuarios de la plataforma para obtener comentarios\r\n desarrollo de materiales de marketing: estudios de casos, publicaciones, etc.\r\n diseño de productos y desarrollo de conceptos\r\n trabajar estrechamente con el equipo de ingeniería, transmitir y explicar conceptos de diseño\r\n \r\nPor qué unirse\r\n rol altamente creativo en una industria de rápido crecimiento (https://www.globenewswire.com/news-release/2022/01...)\r\n ver los resultados de su trabajo utilizados directamente por las principales empresas del mundo\r\n cumplir sus ambiciones y definir directamente cómo se realizará la investigación de materiales en el futuro\r\n trabajar con capital humano de primer nivel en investigación, ingeniería y capital de riesgo\r\n Requisitos\r\nEspecíficos\r\n Título universitario en un campo técnico o experiencia equivalente en la creación o lanzamiento de productos técnicos.\r\n 5 o más años de experiencia desarrollando o lanzando productos/tecnologías en uno o más de los siguientes: Cloud, SaaS, empresas, herramientas internas o redes de cadena de suministro.\r\n 2 o más años de experiencia con Jira, Confluence o herramientas similares\r\n Experiencia liderando la visión del producto, la estrategia de lanzamiento al mercado y las discusiones de diseño\r\n Otros\r\n experiencia creando hojas de ruta estratégicas de productos y trabajando con equipos multifuncionales.\r\n excelentes habilidades de comunicación escrita y oral con capacidad para colaborar eficazmente con la gerencia y el equipo de ingeniería\r\n sólidas habilidades de gestión del tiempo y organización para coordinar múltiples iniciativas, prioridades e implementaciones de nuevas tecnologías y productos en proyectos muy complejos\r\n Capacidad de influir en múltiples partes interesadas sin autoridad directa\r\n sólidas habilidades analíticas y de resolución de problemas\r\n capacidad para aprender y aplicar nuevos conceptos rápidamente\r\n extrema atención al detalle\r\n Adicional\r\n antecedentes previos en software empresarial, ciencia de materiales, química, física o áreas relacionadas\r\n experiencia con aprendizaje automático (machine learning)\r\n Beneficios\r\nBeneficios de la empresa incluyen\r\n Plan de atención médica (médico, dental y visual)\r\n Plan de jubilación (401k, IRA)\r\n Seguro de vida (básico, voluntario y por accidente)\r\n Tiempo libre remunerado (vacaciones, enfermedad y días festivos)\r\n Discapacidad a corto y largo plazo\r\n Capacitación y desarrollo\r\n Trabajo desde casa\r\n Comida y bocadillos gratis\r\n Recursos de bienestar\r\n Plan de opciones de acciones\r\n Compensación\r\n Rango salarial de $120,000 a $180,000\r\n Opciones de acciones del 0.25% al 0.75%\r\n 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