Senior AI Engineer

🕒 Maio 27

🗽 New York – Remoto

🗽 New York – Remote

💵 $150.000 - $160.000 / ano

⏰ Tempo Integral

🟠 Sênior

🤖 Engenheiro de IA

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Macmillan

SiteLinkedInTodas as Vagas

1001 - 5000 funcionários

📱 Mídia

📚 Educação

Media • Education

A Macmillan é uma empresa global de publicação líder e lar de uma ampla gama de selos que publicam ficção, não ficção e materiais educacionais para adultos e crianças. Parte do Holtzbrinck Publishing Group, a Macmillan também opera a Macmillan Learning e a Macmillan Education, fornecendo soluções interativas de cursos, conteúdos para ensino superior, aprendizado de idiomas e publicação de currículos escolares em dezenas de países. A empresa foca em apoiar autores, educadores, estudantes e instituições com conteúdo de classe mundial e ferramentas de aprendizado digital.

Descrição

• Own AI-powered features end-to-end, from scoping, design and requirements engineering to feature evaluation, deployment and operation. • Design, build and maintain cloud-native, event-driven AI applications across the full stack. • Evaluate, integrate, and optimize AI models for production use, balancing quality, latency, reliability and cost. • Collaborate effectively with cross-functional team members, including non-technical stakeholders, to refine requirements and align technical solutions with business objectives. • Build and maintain robust AI inference, evaluation, and monitoring pipelines. • Develop and implement robust, automated AI application evaluation frameworks. • Analyze AI application performance data and experiments, using insights for data-driven improvements. • Operate and improve production systems, taking ownership of reliability, quality, and technical debt. • Stay current with AI advancements and share knowledge to upskill the team. • Plan, track, and break down work effectively in an agile team. • Provide technical leadership, drive design reviews, write ADRs and contribute to hiring and onboarding. • Participate in on-call rotations, incident response and post-mortems for AI-powered systems and help define SLOs and error budgets.

🎯 Requisitos

• Pragmatic, result-oriented analytical problem solving skills that can overcome ambiguity. • Friendly, concise, audience-oriented communication in written and spoken form (English) with effective asynchronous communication. • Self-organized, purpose-driven individual that likes to collaborate with and enable their team. • A T-shaped engineer with strong general software engineering and AI skills, paired with deep expertise in at least one area: Frontend: Advanced experience with React and TS, building high-quality, user-facing apps. Backend: Deep experience designing and operating scalable, event-driven Python systems in cloud-native environments. AI: In-depth knowledge of frontier AI models, evaluation, integration into AI-powered product features, and production best practices. Strong theoretical understanding and practical experience with current AI model internals. • Proven experience with AI model deployment & utilization strategies, evaluation methodologies, and monitoring frameworks in production environments. • Proven experience owning features end-to-end, from technical design to production. • Strong understanding of how to integrate AI into production systems, including the challenges of non-deterministic behavior. • Solid understanding and practical application of MLOps and LLMOps best practices for AI applications. • Familiarity and hands-on experience with major AI service providers and their offerings. • Working knowledge of fine-tuning methods and their appropriate application. • Strong software engineering skills with the ability to bridge AI research/concepts and robust, production-ready engineering implementations. • Experience breaking down complex AI objectives into requirements & actionable tasks. • Experience leveraging and refining agile practices and processes within an AI/ML team context, including effective requirements, design, and code reviews. • Proven experience in quickly assessing and adopting new technologies & frameworks. • Able to implement Clean Architecture & Onion Architecture principles. • Experience building and operating cloud-native systems, ideally on Google Cloud / Firebase with solid DevOps and MLOps fundamentals, including CI/CD, observability, and Infrastructure as Code. • Working knowledge of AI safety and security. • Solid testing discipline across the stack. • Mentorship and technical-leadership experience: growing other engineers, leading design reviews, and influencing technical direction across teams. • Working knowledge of AI safety and security: OWASP Top 10 for LLMs, prompt injection, data exfiltration risks, content moderation, and PII / GDPR handling. • Solid testing discipline across the stack - unit, integration, and contract tests for both deterministic code and AI components. • Experience operating production systems on-call.