Automation QA Engineer NG
Design, develop, and maintain automated test scripts and frameworks to ensure software quality and performance. Collaborate with cross-functional teams to integrate testing into CI/CD pipelines and resolve software defects.
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Design, develop, and maintain automated test scripts and frameworks to ensure software quality and performance. Collaborate with cross-functional teams to integrate testing into CI/CD pipelines and resolve software defects.
The Platform Engineer will design, develop, and maintain robust backend APIs including payment, subscription, and authentication services. They will also collaborate with cross-functional teams to align backend architecture with product strategy and enterprise client needs.
The Site Reliability Engineer will lead incident response, define SLOs, and build automation to ensure platform reliability. They will also partner with engineering teams to implement scalability and observability patterns across distributed systems.
The role involves architecting and managing serverless applications at the edge, maintaining high-performance reverse proxies, and overseeing Kubernetes cluster migrations. Additionally, the engineer will design automated CI/CD pipelines and provide system troubleshooting and incident response for production environments.
The Data Analyst will collect, analyze, and interpret operational and customer data to provide actionable insights for business growth. They will also oversee KPI tracking, dashboard development, and collaborate with cross-functional teams to drive continuous improvement.
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Audit AWS Trainium and NKI tasks to ensure technical accuracy, reproducibility, and rigorous evaluation criteria. Provide actionable feedback on hardware acceleration inefficiencies, kernel execution bugs, and logic errors.
Audit and evaluate GPU kernel tasks to ensure technical accuracy, solvability, and reproducibility within AI training workflows. Provide actionable feedback on memory allocation, execution bottlenecks, and parallel computing logic errors.
Audit AI-assisted developer workflow tasks to ensure they are technically accurate, realistic, and reproducible. Provide actionable feedback on IDE integration faults, coding inefficiencies, and logic errors within the training tasks.
Audit AWS Serverless and Infrastructure as Code tasks to ensure technical accuracy, solvability, and reproducibility for AI training. Provide actionable feedback on deployment pipeline failures, configuration bugs, and architecture logic errors.
Audit machine learning tasks to ensure technical accuracy, solvability, and reproducibility. Provide actionable feedback on data pipeline flaws, model training inefficiencies, and algorithmic logic errors.
Audit and evaluate AI training tasks to ensure technical accuracy, realism, and reproducibility in CVE and application security. Provide actionable feedback on security vulnerabilities, exploit execution, and mitigation logic errors.
Audit Kubernetes tasks to ensure technical accuracy, reproducibility, and rigor for AI training workflows. Provide actionable feedback on orchestration issues, configuration bugs, and logic errors within the tasks.
Audit software engineering tasks to ensure they are technically rigorous, accurate, and reproducible for AI training. Provide actionable feedback on codebase integration issues, test failures, and logic errors.
The developer will build, maintain, and optimize multi-step lead-capture funnels and backend functionality using PHP and MySQL. They will also integrate third-party APIs and implement logging and analytics solutions to drive conversion performance.
Lead the design, architecture, and development of native Windows desktop applications using C# and modern UI frameworks. Collaborate with cross-functional teams to drive feature planning, accessibility efforts, and long-term product roadmaps.
Design and build reusable platform capabilities for LLM applications, AI agents, and RAG workflows. Develop secure integrations and establish standards for AI deployment, observability, and lifecycle management.
You will design and maintain internal tooling and CI/CD pipelines to simplify infrastructure and improve developer productivity. Additionally, you will operate AWS infrastructure and apply SRE principles to ensure system reliability, security, and observability.
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The Lead, Channels and Audit Analytics will design and execute risk-based audits and continuous monitoring routines across digital channels and payment ecosystems. This role involves leveraging advanced data analytics to identify emerging risks, assess control effectiveness, and provide actionable insights to improve business performance.
The Chief Learning Officer will lead a global AI learning agenda and cultivate strategic partnerships with major technology organizations to advance educational transformation. They will also manage a cross-functional AI Circle to foster collaboration and ensure ethical AI adoption across the global network.
You will interact with and evaluate AI models to assess their capabilities, safety, and helpfulness. Your tasks will involve structured conversations, voice-based interactions, and submitting detailed feedback or ratings.
You will interact with and evaluate AI models to assess their capabilities, safety, and helpfulness. Your tasks will involve structured conversations, voice-based interactions, and submitting detailed feedback or recordings.
You will conduct application security assessments, perform threat modelling, and manage vulnerabilities across web and mobile platforms. Additionally, you will collaborate with engineering and product teams to integrate secure development practices and support incident response efforts.
You will own the architecture and lifecycle of critical systems while driving long-term maintainability and technical strategy. Additionally, you will provide mentorship to engineers and collaborate with cross-functional stakeholders to ensure high-quality software delivery.
You will lead the Site Reliability Engineering tooling team to ensure the successful delivery of projects by managing technical planning and team bandwidth. You will also collaborate with stakeholders to refine requirements, maintain high technical standards, and ensure service observability through defined SLIs and SLOs.
The role involves owning the full lifecycle of ML subsystems, from data preparation and training to production deployment. You will build core systems for proactive AI workflows and ensure they meet accuracy, latency, and reliability targets.
The Support Engineer serves as a technical expert troubleshooting Microsoft technologies, network infrastructure, and VoIP systems for clients. They are responsible for managing ticket queues, creating internal documentation, and maintaining high client satisfaction through proactive communication.
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Design and maintain data pipelines to support AI model training and evaluation workflows. Develop automation tools for data collection and labeling while collaborating with ML researchers to improve model performance.
Manage the AI Literacy & Creator Collective programming and develop strategic partnerships with frontier AI companies. Build and scale a global community of educators across platforms like WhatsApp and Discord to foster AI adoption in education.
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