Senior AI Engineer

🕒 il y a 20 jours

🌐 Royaume-Uni, Pays-Bas, +4 autres pays – Distant

🇬🇧 Royaume-Uni – Télétravail 🇳🇱 Pays-Bas – Télétravail 🇮🇪 Irlande – Télétravail 🇷🇴 Roumanie – Télétravail 🇵🇱 Pologne – Télétravail 🇵🇹 Portugal – Télétravail

⏰ Temps Plein

🟠 Senior

🤖 Ingénieur IA

👻 Score fantôme 20%

Ce que ça veut dire : la probabilité que cette offre reste ouverte sans recrutement actif.Comment le lire : 60 % ou plus, on pense que c'est une offre fantôme. Un score plus bas est moins inquiétant.Comment on la calcule : ancienneté, republications, postes ouverts vs taille de l'équipe, rapidité de clôture, et si le salaire est indiqué.À noter : une estimation à partir de données publiques, pas un jugement sur l'entreprise. De vraies offres peuvent avoir un score élevé, alors prenez-le comme un indice, pas comme un fait.

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RWS Group

Site WebLinkedInTous les Emplois

5001 - 10000 employés

💼 Conseil

🏥 Santé

⚖️ Juridique

Consulting • Healthcare • Legal

RWS Group est un leader des services linguistiques et des technologies propulsés par l’IA, spécialisé dans la traduction et la localisation pour une large gamme de secteurs. Axé sur l’amélioration de la communication à l’échelle mondiale, RWS propose des solutions qui améliorent la qualité des traductions, permettent de gérer le contenu multilingue et rationalisent les processus de localisation. Ses services s’adressent à des secteurs tels que l’aéronautique, la finance, le juridique, les sciences de la vie et la technologie, en s’appuyant sur une IA avancée pour permettre à ses clients de se connecter efficacement au‑delà des langues et des cultures.

Description

• 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

🎯 Exigences

• 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

🏖️ Avantages

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