Senior AI Engineer

🕒 Agosto 21

🌐 Reino Unido, Holanda, +4 outros países – Remoto

🇬🇧 Reino Unido – Remoto (RU) 🇳🇱 Holanda – Remoto 🇮🇪 Irlanda – Remoto 🇷🇴 Romênia – Remoto 🇵🇱 Polônia – Remoto 🇵🇹 Portugal – Remoto

⏰ Tempo Integral

🟠 Sênior

🤖 Engenheiro de IA

👻 Score fantasma 38%

O que significa: a chance de ninguém estar realmente contratando para esta vaga.Como ler: 60% ou mais significa que achamos que é uma vaga fantasma. Pontuações mais baixas preocupam menos.Como pontuamos: tempo em aberto, republicações, vagas abertas vs tamanho do time, rapidez para fechar vagas, e se o salário está divulgado.Observação: é uma estimativa de dados públicos, não um julgamento da empresa. Vagas reais podem ter pontuação alta, então use como uma dica, não como um fato.

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RWS Group

SiteLinkedInTodas as Vagas

5001 - 10000 funcionários

💼 Consultoria

🏥 Saúde

⚖️ Jurídico

Consulting • Healthcare • Legal

A RWS Group é uma fornecedora líder de serviços e tecnologias linguísticas impulsionados por IA, especializada em tradução e localização para uma variedade de setores. Com foco em aprimorar a comunicação global, a RWS oferece soluções que elevam a qualidade da tradução, gerenciam conteúdo multilíngue e simplificam o processo de localização. Seus serviços atendem a áreas como aeroespacial, financeiro, jurídico, ciências da vida e tecnologia, aproveitando IA avançada para garantir que os clientes se conectem de forma eficaz entre idiomas e culturas.

Descrição

• Define technical direction for core AI platform components and evaluation systems • Design and architect reliable, scalable, and maintainable platform components • Design reusable abstractions, SDKs, and services for model integration, prompt management, experimentation, and deployment • Define company-wide AI evaluation strategy and methodology • Build production-ready evaluation frameworks and developer tooling • Establish observability standards for AI quality, performance, cost, and regression signals • Build dashboards and reporting that turn AI system signals into actionable decisions • Drive testing discipline, reproducibility, sound experimental design, and statistically defensible model-quality measurement • Lead ambiguous and high-impact technical problems • Mentor engineers through code review, design review, and technical example • Contribute to model and system governance, documentation, versioning, reproducibility, and responsible-AI checks • Codify best practices into tooling and standards adopted by developers across the organization • Track LLM, evaluation research, and AI tooling developments • Prototype and de-risk emerging techniques and tools, moving promising capabilities into production • Champion platform adoption across teams • Partner with research, product, and localization leaders on evaluation methodology and customer needs • Influence roadmap and technical strategy across engineering and product stakeholders • Gather developer requirements and represent them in platform direction • Communicate technical direction, trade-offs, and quality standards to technical and non-technical audiences

🎯 Requisitos

• Significant software engineering experience, typically 5+ years, building and operating production systems, tools, libraries, or services used by many engineers • Excellent API design, reliability, and developer experience • Track record with CI/CD and cloud infrastructure • Proficiency in Python and/or another general-purpose language • Strong testing discipline • Hands-on experience building with LLMs or other ML systems, including prompt engineering, fine-tuning, retrieval, or model integration • Understanding of LLM/ML failure modes and tradeoffs • Proven experience designing and leading evaluation for AI/ML systems • Experience defining metrics and methodology, building evaluation pipelines, managing test sets, and analyzing model quality and regressions • Strong command of accuracy, precision, recall, F1, automated versus human evaluation, statistical significance, and methodological limitations • Excellent written and verbal communication • History of influencing technical direction across teams and mentoring engineers • Comfort with ambiguity and ability to scope, prioritize, and sequence high-impact work with limited direction • Preferred: deep experience evaluating NLP, machine translation, or content-generation systems • Preferred: experience with experimentation and observability tooling, data/test-set versioning, and benchmarking workflows • Preferred: practice in AI governance and documentation, including model cards, system cards, reproducibility, and responsible-AI considerations • Preferred: familiarity with modern LLM ecosystems, orchestration frameworks, and vector stores • Preferred: experience supporting multilingual or localization-focused enterprise products

🏖️ Benefícios

• Equal employment opportunity and non-discrimination commitment • Inclusive work environment • Opportunities for individual growth and career development • Global, culturally diverse work environment

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