Senior Machine Learning Engineer

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Edelman

WebsiteLinkedInAll Job Openings

5001 - 10000 employees

📱 Media

🤝 B2B

🌍 Social Impact

Media • B2B • Social Impact

Edelman is a leading global strategic communications and public relations firm that helps organizations build trust, shape conversations, and manage reputation through data-driven insights, creative campaigns, and digital innovation. The company produces research such as the Edelman Trust Barometer, offers expertise in brand marketing, influencer marketing, social impact and sustainability, and provides advisory services around responsible use of AI and technology. Edelman serves corporate, government and nonprofit clients worldwide to drive reputation, stakeholder engagement, and measurable business outcomes.

📋 Description

• Design, build, and deploy machine learning and GenAI solutions for production use • Develop models and systems across a range of problem types, including structured data, unstructured text, time series, and LLM-powered workflows • Partner with product managers, designers, data engineers, MLOps engineers, and frontend/backend developers to deliver end-to-end product solutions • Work cross-functionally to define ambiguous problems, conduct user discovery, and translate insights into effective product and technical solutions • Evaluate model and system performance using appropriate metrics, and iterate based on results • Contribute to architecture and implementation decisions that balance performance, reliability, scalability, and cost • Document technical approaches, experiments, and implementation details to support maintainability and future development • Communicate technical findings, tradeoffs, and recommendations clearly to both technical and non-technical stakeholders • Help establish best practices for experimentation, model deployment, and AI product development

🎯 Requirements

• 5+ years of experience in machine learning, applied data science, or a related field • Proven experience building and deploying production-ready machine learning systems • Strong experience with Python; familiarity with SQL and data querying workflows • Experience working with structured and unstructured data, including classical ML approaches and modern LLM-based systems • Experience across the ML lifecycle, including problem definition, exploratory analysis, feature or prompt development, model evaluation, deployment, and monitoring • Familiarity with version control and ML/DevOps tooling such as Git and MLflow • Experience working with cloud-based data and ML platforms such as Databricks, AWS, Azure, or GCP • Strong communication skills, including the ability to collaborate with users and non-technical stakeholders throughout discovery and delivery

🏖️ Benefits

• Diversity, equity, inclusion and belonging initiatives • Flexible working arrangements • Professional development opportunities • Collaboration in a supportive environment