Top Tech Jobs & Startup Jobs

The VP Marketing will lead and scale all marketing functions, focusing on demand generation, events, and brand strategy while engaging with enterprise clients.

The Product Manager will develop innovative AI features, collaborate with cross-functional teams, utilize data analytics for decision-making, and engage with the AI community.

Lead and build a full-funnel demand generation and marketing operations function: design multi-channel campaigns (email, paid, content, events, ABM), administer HubSpot, run email programs, own martech stack, instrument funnel reporting and attribution, partner with Sales/RevOps to convert inbound pipeline, and apply AI to improve targeting and execution.

The Senior AI/ML Engineer will develop and improve analytical tools, approaches, and architecture for scalable AI and machine learning solutions, collaborating with engineers and data scientists on innovative projects.

Build, maintain, and improve Swayable's AI/ML and scientific computing systems. Productize machine learning and data-analysis workflows, optimize high-performance distributed and parallel computing, and collaborate with engineers, data scientists, and researchers to deliver scalable, testable solutions and new product features.

This is a general submission role inviting resumes for potential fits in various unspecified positions.

The Sales Director will lead revenue generation from brands and agencies, manage relationships, strategize, and meet sales goals while using CRM software to track progress.

Conduct research pushing experimental and causal-methodologies in public opinion, develop tools and prototypes to analyze experimental data, and communicate findings to internal teams and clients to inform platform features and insights.

Conduct data science research on experimental methodologies and causal modeling, develop tools to analyze experimental data, prototype improvements to platform features, and communicate results to internal teams and external stakeholders to drive product and research decisions.

Conduct data science research advancing experimental and causal methodologies; develop robust tools and prototypes to analyze experimental data; improve core platform features; and communicate findings to internal teams and external stakeholders to drive insights and product improvements.