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.
Expected annual base salary range: $215,000 - $250,000. Actual base salary within that range will be determined by several components including but not limited to the individual's experience, skills, qualifications and job location. For roles located outside of the US, please disregard the posted salary bands as these roles will follow a separate compensation process based on local market comparables.
Responsibilities
Assessment and Strategy — Assess portfolio companies’ technical reality (architecture, data assets, infrastructure, talent), translate findings into strategic insight, contribute to internal memos, and build rapid prototypes to validate proposed strategic moves.
Tooling and Internal Infrastructure — Build and maintain internal tools that make the team more effective: research automation, assessment templates, tracking systems, and reusable components that accelerate work across the portfolio.
Partner Evaluation and Execution Oversight — Lead technical diligence on implementation partners, monitor their delivery during active engagements, and participate in working sessions with portfolio company teams alongside the AI Executive.
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)
Architect, design, implement, verify, and optimize GPU hardware, drivers, features, applications, and tools for next-generation gaming, XR, and AI experiences.
Compensation
$148,300.00 - $222,500.00
Responsibilities
Architect, design, implement, verify, and optimize the structure and performance of critical GPU hardware, drivers, features, applications, and tools
Writes code for complex features, drivers, and APIs using different languages (e.g., C, C++, perl, python) and ensures code will perform effectively on different platforms
Develops and maintains comprehensive pre- and post-silicon tests using advanced tools and methods in different environments (e.g., simulation, emulation, on-device) to ensure optimal performance, stability, security, and identify issues
Identifies deficiencies and proposes solutions to improve designs; implements quality improvements in industry standard APIs and GPU hardware
Collaborates with cross-functional teams, customers, external stakeholders (developers and standards groups), and/or third-party vendors to expose new features and functionality that align with needs and goals for implementation and customization
Requirements
Bachelor's degree in Applied Mathematics, Computer Science, Computer Engineering, Electrical Engineering, Software Engineering, or related field
Master's degree in Applied Mathematics, Computer Science, Computer Engineering, Electrical Engineering, Software Engineering, or related field
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