Top AI & Machine Learning Jobs

As a Machine Learning Scientist, you'll innovate in code analysis using AI and LLMs, develop advanced ML models, and collaborate to enhance software quality assurance.

Design, build, and maintain AI agents and automated marketing workflows. Map automation opportunities, deploy and monitor agents, integrate with marketing tools, produce impact reporting, ensure data governance, and document/enable marketing teams.

Build and maintain AI agents and automated workflows for marketing: identify automation opportunities, design and deploy agents, monitor performance, ensure data governance, integrate with marketing tools, and report efficiency and business impact to leadership.

Design, build, and maintain AI agents and automated workflows for marketing. Identify automation opportunities, deploy and monitor agents, integrate with marketing tools, and report efficiency and business impact. Ensure data quality, privacy, and documentation, and enable marketing teams to adopt automations.

Own and evolve Sonar's AI-native internal platform: design, build, and operationalize agent/connector integrations (Claude/MCP, Rovo), administer and productize Jira Service Management and Atlassian Cloud, implement scalable automations and integrations, maintain CMDB/assets, enforce ITSM/ITIL processes, support security/compliance audits, and partner across teams to drive platform roadmap and stakeholder enablement.

Partner with Marketing to own attribution, ROI, conversion, and funnel analysis. Design experiments, surface proactive insights, optimize marketing spend, and collaborate with Data/Analytics Engineers to build data models and pipelines. Communicate findings and recommendations to non-technical stakeholders.

Partner with Marketing to own attribution, ROI, conversion, and funnel analysis. Design experiments, surface proactive insights, connect spend to outcomes, and collaborate with Data/Analytics Engineers to model marketing data and communicate actionable recommendations.

Develop and research post-training methods for coding-focused LLMs, design and run experiments, build prototypes into products, collaborate with researchers, engineers, and MLOps, and communicate technical results to technical and non-technical audiences.

The role involves pioneering machine learning techniques, developing advanced AI models, building data pipelines, and translating prototypes into products in code analysis.

Research and build post-training solutions for coding LLMs and agentic systems: design experiments, implement policy optimization and fine-tuning methods, translate prototypes into production, and communicate findings across teams.