Senior Machine Learning Engineer
The Washington Post2 months ago
Washington, DC, USASenior
Base Salary
$120k - $199k/yr
Responsibilities
- Design, build, deploy, and operate production ML systems for generative AI, search, Revenue Science, and personalization.
- Translate research models and prototypes into scalable, reliable, and maintainable production systems.
- Build high-throughput, low-latency ranking and retrieval services for personalization, recommendation, search, and intelligent discovery.
- Develop reusable AI/ML platform capabilities for 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.
- Build 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 through batching, caching, quantization, distillation, and hardware-aware optimization.
- Build production systems for semantic and hybrid search, vector retrieval, retrieval-augmented generation, recommendation, and agentic AI workflows.
- Establish ML observability for model quality, data and feature health, latency, throughput, failures, and resource utilization.
- Provide technical leadership through system design, architecture reviews, mentoring, and AI/ML platform roadmap development.
Requirements
- Bachelor’s degree or greater in Computer Science, Computer Engineering, Machine Learning, or a related technical field, or equivalent practical experience.
- At least 5 years of experience in machine learning engineering, software engineering, or building large-scale production ML systems.
- Strong Python programming skills and experience with a production language such as C++, Java, Go, Scala, or Rust.
- Strong knowledge of 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, generative AI, 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 infrastructure as code, such as CloudFormation, CDK, or Terraform.
- Experience mentoring engineers, leading technical projects, and influencing AI/ML platform and architecture roadmaps.
Benefits
- Competitive medical, dental, and vision coverage.
- Company-paid pension and 401(k) match.
- Three weeks of vacation and up to three weeks of paid sick leave.
- Nine paid holidays and two personal days.
- Twenty weeks of paid parental leave for any new parent.
- Mental health resources, backup care, and caregiver concierge services.
- Gender-affirming services and pet insurance.
- Free Post digital subscription.
- Leadership and career development programs.
- Generally on-site five days per week, except for certain newsgathering and business-travel exceptions.
Tech Stack
Categories
About The Washington Post
The Washington Post is a U.S. news organization that publishes national and international reporting across web, mobile apps, and print. It earns revenue from digital and print subscriptions, advertising, events, and licensing its Arc XP publishing platform. Founded in 1877 and headquartered in Washington, DC, it is owned by Nash Holdings, controlled by Jeff Bezos. The Post’s journalism reaches millions of readers and its software powers content sites for media and enterprise customers.