About the role

About The Meridiem

The Meridiem is a fast-growing technology media platform on a mission to deliver timely, high-quality journalism covering AI, startups, venture capital, cybersecurity, and enterprise tech. Built on Next.js 16 and deployed globally on Cloudflare Workers, our platform reaches hundreds of thousands of technology professionals through morning briefings, evening analysis, and breaking coverage across the technology landscape.

Role Overview

We are hiring a Machine Learning Engineer to build intelligent systems that personalize the reader experience and amplify the impact of our journalism. You will develop content recommendation engines, NLP pipelines for automated article tagging and summarization, reader engagement prediction models, and personalization features that help every reader discover the most relevant content. This is a high-impact role where your models will directly shape what hundreds of thousands of people read every day.

Key Responsibilities

• Design and build content recommendation systems that surface relevant articles, briefings, and analysis based on reader interests, behavior, and engagement history.
• Develop NLP pipelines for automated article tagging, entity extraction, topic classification, and content categorization across technology verticals.
• Build reader engagement prediction models that forecast article performance, identify at-risk subscribers, and optimize content distribution timing.
• Create personalization features for the platform — personalized homepages, email digest curation, and "for you" content feeds tailored to individual reader profiles.
• Implement article similarity and semantic search capabilities that enable readers to discover related content and explore topics in depth.
• Design and run A/B tests and online experiments to measure the impact of ML-driven features on reader engagement, retention, and satisfaction.
• Build automated content summarization and headline generation tools that support the editorial team in producing briefings and social media copy.
• Develop and maintain ML infrastructure — feature stores, model serving pipelines, experiment tracking, and monitoring for model drift and performance degradation.
• Collaborate with data engineers to define feature engineering requirements and ensure high-quality training data pipelines.
• Partner with product and editorial teams to identify opportunities where machine learning can enhance the reader experience or improve editorial workflows.
• Stay current with advances in NLP, recommendation systems, and LLM applications relevant to media and publishing.

Requirements

• 4+ years of professional experience in machine learning engineering, with production models serving real users at scale.
• Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow, or JAX) with hands-on experience training and deploying models.
• Deep experience with NLP — text classification, named entity recognition, topic modeling, embeddings, and transformer-based language models.
• Proven track record building recommendation systems — collaborative filtering, content-based methods, or hybrid approaches.
• Experience with ML infrastructure including feature stores, model serving (TFServing, Triton, or similar), experiment tracking (MLflow, Weights & Biases), and CI/CD for models.
• Strong software engineering skills — clean code, version control, testing, and the ability to build production-grade systems, not just notebooks.
• Solid understanding of evaluation metrics, offline/online testing methodology, and the ability to connect model performance to business outcomes.
• Experience working with large text corpora and understanding the nuances of content data — editorial quality, timeliness, topic drift, and audience segmentation.
• Excellent communication skills with the ability to explain model behavior and trade-offs to product managers and editorial stakeholders.

Nice-to-Have

• Experience applying LLMs (GPT, Claude, or open-source models) for content generation, summarization, or classification tasks.
• Background in media, news, or publishing ML applications — recommendation, personalization, or editorial automation.
• Familiarity with edge inference or model deployment on Cloudflare Workers or similar edge compute platforms.
• Experience with real-time ML serving and low-latency prediction requirements.
• Knowledge of privacy-preserving ML techniques and on-device personalization.
• Contributions to open-source ML projects or published research in NLP or recommendation systems.
• Familiarity with Next.js, React, or modern web application architecture.

What We Offer

• Competitive salary ($140,000 - $180,000) with meaningful equity in a Series A startup.
• Fully remote work environment with flexible hours and async-first communication.
• Annual learning and development budget of $3,500 for conferences, courses, compute credits, and research.
• Premium health, dental, and vision insurance coverage.
• Generous PTO policy with company-wide recharge weeks.
• Access to GPU compute resources and any ML infrastructure you need to do your best work.
• The rare opportunity to build ML systems from scratch that directly influence what a large audience of technology professionals reads every day.

How to Apply

Send your resume, links to relevant projects or publications, and a brief note on how machine learning can transform the reader experience in technology journalism to support@themeridiem.com with the subject line "Machine Learning Engineer Application." We review applications on a rolling basis and aim to respond within one week.