Senior ML Engineer: Real-Time News AI & Personalization

washpost; Washington (District of Columbia); On-site; USD 140,000 - 190,000; Full time

Job summary

The Washington Post seeks a senior machine learning engineer to design and scale production AI/ML systems powering journalism, reader experiences, and business goals. You will work on AI/ML platforms, search, retrieval, ranking, and GenAI-powered features in a high-performance environment.

You will partner with Applied Research Scientists to translate research into scalable production systems, focusing on low-latency inference, model serving, and observability.

Qualifications

• Bachelor's degree or higher in Computer Science, Computer Engineering, Machine Learning, or related field, or equivalent practical experience.
• 5+ years of experience in machine learning engineering, software engineering, or building large-scale production ML systems.
• Strong programming skills in Python and experience with a production language such as C++, Java, Go, Scala, or Rust.
• Strong knowledge of software engineering fundamentals, including data structures, algorithms, APIs, distributed systems, testing, and system design.
• Hands-on experience with PyTorch or another modern machine learning framework and deploying deep learning models into production.
• Experience designing and operating end-to-end ML systems, including training, deployment, inference, monitoring, and continuous improvement.
• Strong understanding of low-latency online inference, including CPU/GPU serving, batching, caching, memory utilization, and performance optimization.
• Experience building search, retrieval, ranking, recommendation, GenAI, or related machine learning systems.
• Experience with Kubernetes, Docker, CI/CD, AWS, GCP, Spark, Beam, Kafka, or similar cloud and distributed systems technologies.
• Experience with IaC, such as CloudFormation, CDK, or Terraform.
• Experience mentoring engineers, leading technical projects, and influencing AI/ML platform and architecture roadmaps.

Responsibilities

• Design, build, deploy, and operate production ML systems across generative AI, search, Revenue Science and Personalization.
• Partner with Applied Research Scientists to translate research models and prototypes into scalable, reliable, and maintainable production systems.
• Design and build high-throughput, low-latency ranking and retrieval services supporting real-time personalization, recommendation, search, and intelligent discovery.
• Build and evolve reusable AI/ML platform capabilities for model training, feature generation, experimentation, deployment, inference, model versioning, and monitoring.
• Design and optimize CPU and GPU inference systems for LLMs, embedding models, rerankers, ranking models, and other deep learning workloads.
• Develop scalable online and batch ML architectures for feature pipelines, embedding generation, candidate retrieval, ranking, and model inference.
• Optimize model serving for latency, throughput, reliability, and cost using batching, caching, quantization, distillation, and hardware-aware optimization.
• Build and operate production systems for semantic and hybrid search, vector retrieval, retrieval-augmented generation, recommendation, and agentic AI workflows.
• Establish strong ML observability across model quality, data and feature health, latency, throughput, failures, and resource utilization.
• Provide technical leadership through system design, architecture reviews, mentoring, and shaping the technical roadmap for AI/ML platforms and production systems.

Skills

Python

ML engineering

Distributed systems

PyTorch

End-to-end ML systems

Low-latency inference

Kubernetes

Docker

Cloud platforms

System design

Mentoring engineers

Education

Bachelor's degree or higher in Computer Science/Engineering or related field

Tools

Kubernetes

Docker

CI/CD

AWS

GCP

Spark

Beam

Kafka

Terraform

CloudFormation

Job description

The Washington Post seeks a senior machine learning engineer to design and scale production AI/ML systems powering journalism, reader experiences, and business goals. You will work on AI/ML platforms, search, retrieval, ranking, and GenAI-powered features in a high-performance environment.

You will partner with Applied Research Scientists to translate research into scalable production systems, focusing on low-latency inference, model serving, and observability.