AI Trainer - Kannada - Canada
Perform side-by-side evaluations of Kannada text and voice snippets to assess AI naturalness and authenticity. Provide feedback on tone, pronunciation, and cultural context to improve AI language models.
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Perform side-by-side evaluations of Kannada text and voice snippets to assess AI naturalness and authenticity. Provide feedback on tone, pronunciation, and cultural context to improve AI language models.
Evaluate AI-generated text and voice snippets in Kannada to ensure naturalness, authenticity, and cultural accuracy. Provide detailed feedback and data tagging to improve the nuance and tone of AI communication.
Perform side-by-side evaluations of Kannada text and voice snippets to assess naturalness and authenticity. Provide feedback on AI-generated audio regarding tone, pronunciation, and cultural context.
Perform side-by-side evaluations of Kannada text and voice snippets to assess AI naturalness and authenticity. Provide feedback on tone, pronunciation, and cultural context to improve AI language models.
Perform side-by-side evaluations of text and voice snippets to assess the naturalness and authenticity of AI-generated Kannada speech. Provide feedback on tone, pronunciation, and cultural context to improve AI model accuracy.
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Evaluate AI-generated text and voice snippets in Kannada to ensure naturalness, authenticity, and cultural accuracy. Provide feedback through data tagging and side-by-side comparisons to improve AI communication nuances.
Evaluate AI-generated text and voice snippets in Kannada to ensure naturalness, authenticity, and cultural accuracy. Provide detailed feedback and data tagging to improve the nuance and tone of AI communication models.
Evaluate AI-generated text and voice snippets in Kannada to ensure naturalness, authenticity, and cultural accuracy. Provide detailed feedback and data tagging to improve the nuance and tone of AI communication.
Evaluate AI-generated text and voice snippets in Kannada to ensure naturalness and cultural authenticity. Provide feedback through data tagging and side-by-side comparisons to improve AI communication nuances.
Manage and develop existing customer relationships and acquire new clients for 2D, 3D, and AI solutions in the DACH North region. Responsible for the entire sales cycle, including offer creation, contract negotiations, and lead/forecast management.
Own the platform-wide data and AI infrastructure, including data modeling, storage, and governance. Design and build the shared data layer that powers analytics, search, recommendations, and agentic AI products.
Lead and scale the AI and automation strategy across the customer experience landscape to improve resolution rates and brand loyalty. Manage a technical team and oversee the architecture of chatbot and agent-facing tools while ensuring AI governance and vendor performance.
Translate customer business goals into platform value narratives and design enterprise-ready architectures for software-defined automation and Physical AI. Act as a trusted advisor to bridge the gap between executive ambition and technical reality during the sales and early adoption journey.
Act as a mentor and coach for participants in an AI Software Engineering Bootcamp, providing technical guidance and code reviews. Collaborate with top trainers to develop learning materials and support students through all phases of the program.
Develop and maintain Python-based applications while designing and optimizing Generative AI solutions for business use cases. Collaborate with stakeholders to deliver scalable AI models and maintain comprehensive technical documentation.
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Design and scale production-grade AI applications and intelligent agents to drive measurable business outcomes for customers. Lead technical engagements and provide feedback to Engineering to influence the AI product roadmap.
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Design and maintain an enterprise AI platform focusing on LLM routing, agentic workflows, and RAG components. Build scalable deployment pipelines using Kubernetes and ArgoCD to empower developers to deploy AI-driven solutions.
Research and implement state-of-the-art Gen AI and ML solutions to solve complex National Security problems for customers. Translate real-world challenges into reusable solution recipes and platform capabilities to evolve Snorkel's AI tooling.
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Define and evolve the technical architecture for Caseware's AI platform, focusing on scalable and secure AI capabilities. Design and operate AI systems using LLMs, agentic workflows, and governance frameworks to solve customer problems.
Lead end-to-end solution selling motions to drive adoption of the Atlassian Teamwork Collection across named enterprise accounts. Collaborate cross-functionally with GTM teams and provide customer insights to engineering to shape the product roadmap.
Lead the strategy and implementation of AI-powered customer support tools and automation to improve operational efficiency and self-service adoption. Manage the Zendesk platform and the evolution of internal and external knowledge bases to ensure accurate and accessible content.
Build an AI-native operator command center for restaurants to automate operational workflows and drive business outcomes. Own the foundations for orders, menus, and integrations to ensure a trustworthy and scalable product experience.
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Record short video and audio clips using various tones and emotional styles to help AI understand human intent. Additionally, transcribe audio and video clips into text.
The role involves creating authoritative content on frontier AI and LLMs to build a category narrative for the insurance industry. Responsibilities include writing thought leadership, web copy, and ghostwriting for the CEO to make complex technical capabilities legible to senior executives.
Lead the design and deployment of enterprise-scale AI and data solutions, focusing on agentic AI workflows and scalable data pipelines. Collaborate with cross-functional stakeholders to ensure solutions meet business objectives and financial industry compliance standards.
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