• Research and design AI systems, models, and advanced machine learning algorithms to augment physics-driven modeling and simulation systems and enable intelligent AI agents to reason, plan, and adapt based on simulated and real-world sensor data • Lead innovation in AI-driven simulation tooling, identifying opportunities to enhance workflows through reinforcement learning, multi-agent systems, and hybrid modeling approaches • Collaborate with research, engineering, and product teams to build AI-driven solutions that meet mission-critical modeling and decision-support needs • Publish, and present research outcomes at approved conferences and peer-reviewed journals sharing advances with both internal stakeholders and the wider research community. • Contribute content to technical invention disclosures, including associated narrative, graphics, and engagements in support of patent development • Perform additional responsibilities (no more than 10% of duties) in support of the company’s data science and product development initiatives

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description We are seeking Language Annotation Experts for Dutch. In this role, you’ll contribute to the development of advanced Voice AI models by providing linguistic expertise, creating and refining annotation conventions, and supporting high-quality data collection efforts. - Develop and apply annotation guidelines tailored to your language of expertise - Label and annotate speech, text, and phonetic data with accuracy and consistency - Provide linguistic insights into pronunciation, prosody, and grammar usage - Support data collection processes, ensuring high-quality and culturally relevant datasets - Collaborate with the product and research teams to refine voice models - Perform quality checks on annotated data to ensure consistency and correctness Qualifications - Native Dutch speaker - English language proficiency - Strong background in linguistics, phonetics, computational linguistics, or related field - Experience with data annotation, transcription, or linguistic QA - Familiarity with annotation tools and workflows is a plus - Attention to detail and ability to follow complex guidelines - Comfortable working independently in a remote, collaborative environment Requirements - Prior experience contributing to speech/voice technology projects (Nice to Have) - Understanding of NLP, ASR, or TTS systems (Nice to Have) - Multilingual proficiency (Nice to Have) Benefits - Remote, flexible work - Opportunity to directly influence the future of Voice AI - Work with a diverse, mission-driven team passionate about language and technology Company Description Rime AI is building next-generation voice technology to make human–computer interactions more natural, accurate, and expressive. Our platform powers high-quality speech experiences across industries, and we’re looking for passionate language experts to help us improve the way our AI understands and speaks the world’s languages.

• Develop automation to support penetration tests and red-team style assessments across networks, endpoints, identity, and web apps; produce actionable, mission-aligned findings and remediation guidance. • Leverage agentic workflows to utilize common offensive tools: • Research and prototype ML/RL approaches for security (e.g., attack-path selection, exploit prioritization, automated decision policies), and evaluate them via measurable experiments and test environments. • Build automation around offensive workflows (repeatable test harnesses, lab environments, tooling wrappers, and data collection for ML/RL experiments). • Collaborate with defensive engineers/researchers to translate findings into detections, mitigations, and secure-by-design improvements.

• Evaluate emerging agentic patterns (multi-agent coordination, tool use, human-in-the-loop oversight) • Implement them as working systems and build reusable automation and integration patterns • Create deployment automation for agentic services: reproducible environments and repeatable enterprise releases on Kubernetes • Debug and refine AI-driven workflows, ensuring work can be generalized • Research and apply nonhuman/workload identity patterns for agentic services and integrate into deployment automation