Senior ML Engineer: Scalable GenAI & Personalization

Nashville Public Radio; Washington (District of Columbia); On-site; USD 120,000 - 199,000; Full time

Benefits offered by this job

Medical, dental, vision

Company-paid pension and 401(k) match

Vacation and sick leave

Paid parental leave

Mental health resources

Job summary

The Washington Post is seeking a senior machine learning engineer to design, build, and scale production AI/ML systems powering the next generation of journalism. This role centers on AI/ML platforms, search, retrieval, ranking, recommendation, and generative AI-powered reader experiences.

You will translate advanced AI/ML research into reliable, low-latency production systems serving journalism, readers, and business goals, collaborating across teams and maintaining high observability and

Qualifications

• Bachelor’s degree or greater in Computer Science, Computer Engineering, ML, or related technical field, or equivalent practical experience.
• 5+ years of experience in machine learning engineering or building large-scale production ML systems.
• Strong programming skills in Python and production languages (C++, Java, Go, Scala, or Rust).
• Hands-on experience with PyTorch or equivalent and deploying DL models to production.
• Experience designing end-to-end ML systems, training, deployment, inference, monitoring, and improvement.
• Strong understanding of low-latency online inference, CPU/GPU serving, batching, caching, and performance optimization.
• Experience building search, retrieval, ranking, recommendation, GenAI, or related ML systems.
• Experience with Kubernetes, Docker, CI/CD, AWS, GCP, Spark, Beam, Kafka, or similar cloud and distributed systems technologies.

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 into scalable, reliable production systems.
• Design and build high-throughput, low-latency ranking and retrieval services for real-time personalization and discovery.
• Build reusable AI/ML platform capabilities for training, feature generation, experimentation, deployment, inference, versioning and monitoring.
• Design and optimize CPU and GPU inference systems for LLMs, embedding models, rerankers, and other DL 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 via batching, caching, quantization, distillation, and hardware-aware optimization.
• Build and operate production systems for semantic/hybrid search, vector retrieval, retrieval-augmented generation, recommendation, and agentic AI workflows.
• Establish strong ML observability across model quality, data/feature health, latency, throughput, failures and resource utilization.
• Provide technical leadership through system design, architecture reviews, mentoring, and shaping the AI/ML roadmap.

Skills

Python

PyTorch

Low-latency inference

C++/Java/Go/Rust

Distributed systems

Model deployment

Kubernetes

Docker

AWS/GCP

CI/CD

SQL/NoSQL

Education

Bachelor’s degree in Computer Science, Computer Engineering, or related field

Tools

Kubernetes

Docker

CI/CD

AWS

GCP

Spark

Beam

Kafka

Terraform

Job description

The Washington Post is seeking a senior machine learning engineer to design, build, and scale production AI/ML systems powering the next generation of journalism. This role centers on AI/ML platforms, search, retrieval, ranking, recommendation, and generative AI-powered reader experiences.

You will translate advanced AI/ML research into reliable, low-latency production systems serving journalism, readers, and business goals, collaborating across teams and maintaining high observability and