Job description

Job Description: POLITICO is seeking a Machine Learning Engineer to help build the next generation of AI-powered newsroom and product capabilities. As we expand into new sector products, new professional audiences and new geographies under our Go-Forward Growth Strategy, POLITICO is investing in machine learning systems that go beyond simply integrating foundation models. This role will work alongside software engineers, product managers, journalists and editorial leadership to develop models, evaluation frameworks and data pipelines that apply POLITICO s editorial expertise across AI-powered tools and improve newsroom and product workflows. The ideal candidate is excited about applying machine learning in support of journalism. You ll work closely with software engineers, journalists and product teams to develop AI-powered tools and data products that strengthen reporting, improve newsroom workflows and help bring POLITICO s editorial expertise to a broader audience. What You ll Do: Design, build and deploy production machine learning systems that support newsroom, editorial and new-audience initiatives. Develop classification, prediction and ranking models using proprietary newsroom data and editorial expertise — a modeling foundation that extends across new sector products (Decoded, Code & Counsel, Energy, Pharma) rather than requiring a bespoke build per vertical. Build datasets, feature engineering pipelines and evaluation frameworks to improve AI system performance, including turning the Leadership team s data-needs definitions into working systems. Experiment with prompting, retrieval, fine-tuning and other model adaptation techniques to solve journalism-specific problems. Partner closely with journalists and editors to translate editorial knowledge into machine learning features, labels and evaluation criteria. Collaborate with software engineers to integrate machine learning capabilities into production applications. Measure and improve model quality using rigorous evaluation methodologies that balance accuracy, editorial standards and operational performance. Evaluate new AI technologies while considering performance, cost, maintainability and long-term flexibility. Example Projects: You may work on initiatives such as: Building systems that classify the newsworthiness of stories using editorial judgment. Developing prediction models that combine public information with POLITICO s proprietary reporting expertise — the same approach that powers POLITICO Signals and Agency IQ. Improving AI-assisted editing by helping models better understand and apply POLITICO s editorial style guide. Creating proprietary classifiers that enrich public datasets with editorial intelligence, extendable to new sector products as they launch. Designing evaluation frameworks to measure AI quality before newsroom deployment. Optimizing AI workflows to improve performance while reducing inference costs. Supporting investigative and enterprise reporting through machine-learning-assisted analysis of complex datasets. What You ll Need: Required 5 years of professional experience building or deploying machine learning systems. Strong software engineering skills, preferably in Python. Experience with machine learning fundamentals including supervised learning, feature engineering, model evaluation and experimentation. Experience with modern machine learning frameworks such as PyTorch or TensorFlow. Familiarity with large language models, embeddings or natural language processing techniques. Experience working with structured and unstructured data. Strong problem-solving and analytical skills. Excellent communication skills and the ability to collaborate with engineers, product managers and non-technical stakeholders. Preferred Experience adapting or fine-tuning foundation models. Experience building NLP, information retrieval, classification or ranking systems. Familiarity with model evaluation frameworks, experiment tracking or MLOps practices. Experience deploying machine learning models to cloud infrastructure. Interest in journalism, media, public policy or knowledge-intensive domains. What Success Looks Like in the First Year: Improve the accuracy and reliability of AI systems used by POLITICO s newsroom. Build evaluation frameworks that help teams confidently assess AI quality and editorial alignment. Contribute to proprietary classifiers, prediction systems and editorial intelligence capabilities that differentiate a named initiative — a sector product, POLITICO Signals or Agency IQ. Partner effectively with software engineers, product teams and newsroom stakeholders to bring machine learning solutions into production. Help establish a strong technical foundation for future AI initiatives across the newsroom and our new lines of business. COMPENSATION: $175,000 - $225,000 Annual Base. The final salary offered will be based on factors including relevant experience, skills, and qualifications. We value our people. Click here for more on what we offer and what it’s like to work for POLITICO. Let’s keep in touch. You can view our list of open positions here . We hope to see your application soon! About Us. POLITICO illuminates the forces shaping global power. Since 2007, we have delivered intelligence that anticipates tomorrow s headlines, not reports on yesterday s news. As politics has increasingly become the defining force of our era, our work has never been more vital. Cabinet secretaries and Ministers start their mornings with our analysis. CEOs shape strategy around our reporting. Advocacy leaders rely on our insights to move policy. We deliver the straightforward facts and clear-eyed analysis they need to navigate the most complex political landscape of our lifetimes. Our 1,100 publishing professionals across the world s key democratic capitals—Washington, Brussels, London, Paris, Berlin, Sacramento, and New York—form the world s premier politics and policy newsroom. We tell the story of how power really works by explaining who wields it and how they plan to exercise it, connecting dots others miss and delivering scoops from sources others don t even know exist. Innovation has always been a core tenet of our story. At launch, we bet that depth would trump scale, that talent would trump traffic, and that politics would become central to modern life. In 2011, we made another bet and launched POLITICO Pro to help decision-makers understand the business of government, transforming both how they shape government action and the business of journalism itself. These bets have made POLITICO the most successful digital news startup of its generation and the indispensable resource for leaders who shape the future. Today, we are a rarity in media: a growing, profitable, and sustainable news organization. POLITICO is a subsidiary of Axel Springer SE, a family-owned transatlantic media company headquartered in Berlin and New York. Axel Springer is dedicated to shaping the future of journalism in the free world, believing that a free and informed society is essential to democracy. The company’s guiding principles - first articulated as The Essentials by founder Axel Springer in the aftermath of World War II - remain a cornerstone of the company’s foundation today. Learn more about Axel Springer . Posting date: 2026-10-09 Title: Machine Learning Engineer

Requirements

Must-haves

What You ll Do: Design, build and deploy production machine learning systems that support newsroom, editorial and new-audience initiatives.
Build datasets, feature engineering pipelines and evaluation frameworks to improve AI system performance, including turning the Leadership team s data-needs definitions into working systems.
Experiment with prompting, retrieval, fine-tuning and other model adaptation techniques to solve journalism-specific problems.
Partner closely with journalists and editors to translate editorial knowledge into machine learning features, labels and evaluation criteria.
Collaborate with software engineers to integrate machine learning capabilities into production applications.
Measure and improve model quality using rigorous evaluation methodologies that balance accuracy, editorial standards and operational performance.
Evaluate new AI technologies while considering performance, cost, maintainability and long-term flexibility.
Example Projects: You may work on initiatives such as:
Building systems that classify the newsworthiness of stories using editorial judgment.
Developing prediction models that combine public information with POLITICO s proprietary reporting expertise — the same approach that powers POLITICO Signals and Agency IQ.
Improving AI-assisted editing by helping models better understand and apply POLITICO s editorial style guide.
Creating proprietary classifiers that enrich public datasets with editorial intelligence, extendable to new sector products as they launch.

Nice-to-haves

Experience adapting or fine-tuning foundation models.
Experience building NLP, information retrieval, classification or ranking systems.
Familiarity with model evaluation frameworks, experiment tracking or MLOps practices.
Experience deploying machine learning models to cloud infrastructure.
Interest in journalism, media, public policy or knowledge-intensive domains.
What Success Looks Like in the First Year: Improve the accuracy and reliability of AI systems used by POLITICO s newsroom.
Build evaluation frameworks that help teams confidently assess AI quality and editorial alignment.
Contribute to proprietary classifiers, prediction systems and editorial intelligence capabilities that differentiate a named initiative — a sector product, POLITICO Signals or Agency IQ.
Partner effectively with software engineers, product teams and newsroom stakeholders to bring machine learning solutions into production.
Help establish a strong technical foundation for future AI initiatives across the newsroom and our new lines of business.
COMPENSATION: $175,000 - $225,000 Annual Base. The final salary offered will be based on factors including relevant experience, skills, and qualifications.
We value our people. Click here for more on what we offer and what it’s like to work for POLITICO.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

machine learningaigopython

Platform: workday
Effort: long