The Samizdat team manages the New York Times' GraphQL platform, providing an API layer powering products and internal systems during a period of modernization and scale.
Compensation
The annual base pay range for this role is between: $162,000—$195,000 USD
Responsibilities
Develop new platform offerings while ensuring the reliability, scalability, and performance of our GraphQL platform as it continues to grow.
Lead by example in establishing and enforcing GraphQL schema design and governance best practices, participating in platform-wide schema working groups, and reviewing/mentoring cross-team contributions.
Contribute to the platform's automation, developer tooling, and onboarding/kick-off guides for service adopters and subgraph contributors.
Support on-call, incident response, and troubleshooting efforts for platform-level escalations.
Mentor team members, promoting technical excellence and a culture of respect and constructive feedback.
Design, develop, test, and maintain end-to-end web applications using Java, Spring Boot, JavaScript/TypeScript, HTML, CSS, and Lit-based web components, while integrating with Adobe Experience Manager and deploying cloud-native services on AWS.
Compensation
Pay Range: $50-53/Hour on W2/C2C (All Inclusive)
Responsibilities
Design, develop, test, and maintain end-to-end web applications using Java, Spring Boot, JavaScript/TypeScript, HTML, CSS, and Lit-based web components.
Build reusable, accessible, responsive, and standards-based UI components using Lit and native Web Components.
Design and implement secure REST and event-driven APIs and integrate applications with enterprise and third-party systems.
Develop cloud-native services on AWS using appropriate compute, storage, database, integration, security, and observability services.
Create and support microservices deployed through containers and serverless patterns, based on solution needs.
Senior-level engineering role focused on developing, designing, and maintaining application software and services, leading code reviews, and mentoring junior engineers within the OCI environment.
Compensation
US: Hiring Range in USD from: $86,100 to $187,000 per annum. May be eligible for bonus and equity.
Responsibilities
Adheres to and suggests improvements to all phases of the application software development lifecycle
Develops new application features and enhancements following design specifications
Leads code reviews in designated application areas to help drive improvements
Conducts debugging and troubleshooting to identify and fix moderately complex application issues
Troubleshoots and resolves moderately complex issues related to API functionality, integration, and service-to-service interactions
AI Platform and MLOps Engineer responsible for infrastructure, integrations, observability, and developer tools to operationalize AI for vehicle design, manufacture, flight test, and business teams.
Compensation
$142,000-$165,000
Responsibilities
Design, deploy, and operate reliable infrastructure for ML, LLM, and RAG workloads
Host, maintain, monitor, and optimize RAG systems
Serve as a subject matter expert for MLOps and AI workload operations
Integrate and support COTS products, third-party services, open-source tools, and custom AI capabilities
Develop APIs, plugins, and reusable integrations for AI capabilities
Requirements
BS in Computer Science, Engineering, Data Science, or a related field
Nice to have: MLOps experience
Nice to have: LLM and RAG system optimization
Nice to have: AWS services such as EC2, Lambda, ECS, EKS, S3, CloudWatch
Build and ship AI systems that power Checkr’s core products, owning ML services end-to-end and integrating LLMs and APIs into production.
Locations (2)
Denver, Colorado, United States
San Francisco, California, United States
Compensation
On-target Earnings OR Base Salary range (San Francisco, CA) $207,000—$244,000 USD On-target Earnings OR Base Salary range (Denver, CO) $176,000—$207,000 USD
Responsibilities
Build and deploy ML/AI services
Design, develop, and ship ML models and AI systems
Write model code, API layer, monitoring, and tests
Partner with product and engineering to translate business problems into ML solutions
Define API contracts with product engineers
Requirements
Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related technical field, or equivalent depth from experience
Nice to have: MLOps platforms (MLflow, SageMaker, Vertex)
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