Search the 8 jobs at Cognism

The Customer Marketing Manager at Cognism will drive upsell growth within the existing customer base by planning and executing multi-channel demand generation strategies. Responsibilities include campaign management, strategic planning, data analysis, and cross-functional collaboration to enhance customer engagement and retention efforts.

As a Customer Expansion Manager at Cognism, you will lead demand generation strategies to drive upsell growth within the existing customer base. Responsibilities include developing multi-channel campaigns, analyzing performance data, and optimizing marketing efforts through collaboration with cross-functional teams.

The Senior MLOps Engineer will build and manage automation pipelines, design cloud architectures, ensure MLOps best practices, and collaborate with Data Scientists to integrate AI/ML models. Responsibilities include optimizing ML services, monitoring production workloads, and implementing MLOps frameworks and tools on cloud platforms.

The Senior MLOps Engineer role involves building and managing automation pipelines for ML platforms, designing architectures on AWS, ensuring MLOps best practices, and collaborating closely with Data Scientists for model deployment and monitoring. The position focuses on optimizing and enhancing ML service quality and scalability while implementing efficient workflows.

The Senior MLOps Engineer at Cognism will optimize ML services, build automation pipelines, implement architectures on AWS, enforce best practices, and maintain production-critical ML systems, acting as a bridge between AI and Engineering teams.

The Content Manager will develop and execute a multimedia content strategy, create various content formats, activate campaigns across platforms, ensure SEO optimization, and report on engagement and contribution to revenue. This role requires collaboration with multiple stakeholders and expertise in content marketing and demand generation.

As a Senior MLOps Engineer at Cognism, you will build and manage automation pipelines, implement secure cloud architectures, and contribute to MLOps best practices. You will collaborate with Data Scientists and maintain production ML services, ensuring scalability and reliability.

The Senior MLOps Engineer will enhance ML services by optimizing workflows, building automation pipelines, designing cloud architectures, and collaborating with Data Scientists. Responsibilities include deploying ML models, ensuring service reliability, and implementing best practices in MLOps.