Weekday AI

Collaborate with teams to design and evaluate AI training infrastructure and ensure production reliability and security. | 4+ years in Cloud/DevOps/SRE with Kubernetes and Infrastructure-as-Code expertise, strong AWS skills, and troubleshooting distributed systems. | This role is for one of our clients Compensation: $75 - $110 per hour We are seeking an experienced Cloud / DevOps Engineer (Infra & IaC) to contribute to a cutting-edge GenAI environment focused on building and improving large-scale AI training and inference infrastructure. The ideal candidate will bring strong, hands-on expertise in Kubernetes, AWS cloud services, Infrastructure-as-Code (IaC), and CI/CD. You will apply your real-world infrastructure engineering experience to evaluate technical workflows, create high-quality reference solutions, identify gaps in AI-generated outputs, and help establish rigorous standards for cloud and DevOps reasoning. This is a full-time engagement requiring 40 hours per week, Monday through Friday. Key Responsibilities Collaborate with research and engineering teams to identify knowledge gaps and improve AI model performance across cloud infrastructure, DevOps, Kubernetes, and Infrastructure-as-Code domains. Design realistic and technically challenging tasks covering Kubernetes troubleshooting, AWS service integration, infrastructure automation, and production operations. Develop accurate, detailed reference solutions for complex infrastructure engineering scenarios. Review and evaluate AI-generated technical solutions for correctness, reliability, scalability, security, and adherence to production best practices. Provide clear, structured written feedback highlighting technical gaps, incorrect assumptions, and opportunities for improvement. Create detailed evaluation criteria, rubrics, and benchmarks for assessing Kubernetes troubleshooting, IaC architecture, AWS integrations, and CI/CD reasoning. Develop scenarios involving cluster failures, infrastructure automation, deployment workflows, service integrations, and operational reliability. Work closely with other technical subject matter experts to maintain consistency, accuracy, and quality across evaluation datasets. Translate practical production experience into structured guidance that can be used to improve AI-generated infrastructure solutions. Core Qualifications 4+ years of professional experience in Cloud Infrastructure, DevOps, Site Reliability Engineering, Platform Engineering, or a closely related field. Strong hands-on experience managing Kubernetes in production environments, including diagnosing, troubleshooting, and resolving cluster failures and operational issues. Experience with Kubernetes beyond simply writing manifests or consuming managed Kubernetes control planes. Proven production experience with Infrastructure-as-Code, particularly Terraform and/or AWS CDK. Strong practical knowledge of AWS cloud services, including production integration with services such as: AWS Lambda API Gateway DynamoDB Experience designing, implementing, and maintaining CI/CD pipelines for production workloads. Strong understanding of cloud architecture, infrastructure automation, deployment strategies, observability, reliability, and operational best practices. Demonstrated career progression with increasing ownership and responsibility in infrastructure, DevOps, or platform engineering. Ability to commit reliably to 40 hours per week during standard weekdays. Excellent written and verbal communication skills, with the ability to explain complex technical concepts and engineering decisions clearly. Strong analytical and troubleshooting abilities, particularly when diagnosing distributed systems and infrastructure failures. Preferred Skills Experience working with large-scale cloud infrastructure or highly distributed systems. Familiarity with Kubernetes networking, security, storage, scaling, and cluster lifecycle management. Experience implementing infrastructure security and reliability best practices. Knowledge of AWS architecture patterns and cloud-native application design. Experience with GitOps, containerization, monitoring, logging, and observability platforms. Familiarity with modern DevOps and platform engineering methodologies. Experience reviewing or evaluating technical documentation, engineering solutions, or AI-generated outputs. What You’ll Contribute In this role, your production infrastructure expertise will help establish high-quality standards for AI systems working with complex Cloud, DevOps, Kubernetes, AWS, and IaC problems. You will play a key role in transforming practical engineering knowledge into structured tasks, reference solutions, evaluation frameworks, and high-quality technical feedback that can improve the capabilities of next-generation AI models. Equal Opportunity We are committed to providing equal employment opportunities to all qualified candidates. Employment decisions are made without regard to legally protected characteristics, and reasonable accommodations are available throughout the hiring and engagement process upon request.

Evaluate AI-generated artifacts for quality and provide structured feedback. | 5+ years market research experience, proficiency in Microsoft Office and Google Workspace, postgraduate degree required. | This role is for one of our clients Compensation: $80-$120 per hour We are hiring expert Evaluators in Market research / competitive intelligence to review and assess AI-generated work products (documents, spreadsheets, and slide decks) for accuracy, rigor, and domain quality. You will apply deep subject-matter expertise to grade outputs. This is a remote, hourly engagement. Requirements (must have) 5+ years of relevant professional experience in Market research / competitive intelligence. Native or professional fluency in English. Highly proficient in Microsoft Office and Google Workspace, especially Slides (Google Slides / PowerPoint). Preferred (nice to have) Advanced degree (Master's or higher) from a reputable institution. What you'll do Evaluate AI-generated artifacts against domain-specific quality rubrics. Identify factual, aesthetic, and presentation errors. Provide clear, structured written feedback. We consider all qualified applicants without regard to legally protected characteristics and provide reasonable accommodations upon request. Contract and Payment Terms You will be engaged as an independent contractor. This is a fully remote role that can be completed on your own schedule. Projects can be extended, shortened, or concluded early depending on needs and performance. Your work will not involve access to confidential or proprietary information from any employer, client, or institution. Payments are weekly on Stripe or Wise based on services rendered. Please note: We are unable to support H1-B or STEM OPT candidates at this time.

Design, develop, and ship full-stack applications and backend services integrating AI model capabilities while collaborating with engineering teams. | 3+ years professional software development experience with proficiency in at least one major programming language and full-stack development, cloud infrastructure experience, and ability to work in fast-paced environments. | This role is for one of our clients Compensation: $50-$65 per hour Join a leading AI research organization's cutting-edge GenAI team and contribute to the development of next-generation AI models and applications. We are seeking talented Full-Stack Software Engineers with hands-on production experience across modern software ecosystems, including Python, Java, Rust, C#, C++, and TypeScript. In this role, you will build, integrate, and stress-test production-quality software that leverages advanced AI models. You will work closely with engineering leadership on fast-moving projects, adapt quickly to evolving requirements, and contribute working code with minimal ramp-up. This is a full-time opportunity requiring approximately 40 hours per week, primarily during weekdays. 2. Key Responsibilities Design, develop, and ship full-stack applications, backend services, internal tools, and integrations using technologies such as Python, Java, Rust, C#, C++, and TypeScript. Build software that exercises and integrates advanced AI model capabilities across end-to-end workflows. Integrate model APIs into production-ready applications, including supporting infrastructure such as tool interfaces, evaluation frameworks, monitoring, and telemetry. Develop scalable backend services and APIs while contributing to modern front-end applications. Investigate and troubleshoot model, application, and integration issues, documenting failure modes and technical findings clearly. Translate engineering observations into actionable feedback for research and engineering teams. Rapidly prototype solutions and deliver functional increments in environments with evolving requirements and limited initial specifications. Collaborate with engineering managers and fellow developers to maintain high standards for code quality, architecture, testing, and technical documentation. Work across unfamiliar systems and codebases, quickly identifying dependencies and implementing effective solutions. 3. Core Qualifications 3+ years of professional experience building and deploying production software in a high-quality engineering environment. Strong production experience in at least one of Python, Java, Rust, C#, or C++, along with working proficiency in a second programming language. Hands-on full-stack development experience spanning: Backend services and APIs React or another modern front-end framework Relational or document databases Cloud deployment and infrastructure Experience designing, developing, testing, and deploying software end to end. Demonstrated ability to quickly understand unfamiliar codebases, development environments, and technical architectures. Strong problem-solving skills and the ability to work effectively in fast-changing technical environments. Demonstrable professional growth and increasing technical responsibility. Strong written and verbal communication skills, with the ability to explain complex technical decisions clearly. Ability to commit reliably to 40 hours per week during weekdays. 4. Ideal Candidate The ideal candidate is a hands-on software engineer who enjoys solving complex technical problems, learning new technologies quickly, and building production-quality systems from the ground up. Experience working with AI/ML systems, model APIs, developer tooling, evaluation infrastructure, or AI-powered applications is a plus, but strong software engineering fundamentals and full-stack production experience are the primary requirements. Equal Employment Opportunity We are committed to providing equal employment opportunities to all qualified applicants. We do not discriminate based on race, religion, color, national origin, sex, sexual orientation, gender identity or expression, age, disability, veteran status, genetic information, or any other legally protected characteristic.

Build and maintain full-stack applications and backend services integrating AI models and ensuring system reliability. | 6+ years professional software engineering with strong expertise in major programming languages and full-stack capabilities including backend, frontend, and cloud deployment. | This role is for one of our clients Compensation: $90-$110 per hour Join a leading AI research organization at the forefront of generative AI and contribute to the development and evaluation of advanced Large Language Models. We are seeking experienced Senior Full-Stack Software Engineers with strong production expertise across modern software ecosystems, including Python, Java, Rust, C#, C++, and TypeScript. In this role, you will build, integrate, and stress-test production-quality software that interacts with frontier AI models. You will work closely with engineering and research teams on fast-moving initiatives, rapidly adapt to new codebases and requirements, and contribute working code early in the engagement. This is a full-time role requiring 40 hours per week. 2. Key Responsibilities Build full-stack applications: Design, develop, and ship production-quality applications, backend services, APIs, and internal tools using technologies such as Python, Java, Rust, C#, C++, and TypeScript. Integrate AI models: Integrate pre-release and frontier model APIs into functional software systems, including tool interfaces, evaluation frameworks, telemetry, and supporting infrastructure. Develop across the stack: Work across backend services, APIs, databases, frontend applications, cloud infrastructure, and deployment environments to deliver complete solutions. Test and stress-test systems: Build applications and testing frameworks that exercise model capabilities and identify performance, reliability, integration, and usability issues. Identify failure modes: Diagnose technical and model-related failures encountered during development and document findings clearly for engineering and research teams. Prototype rapidly: Translate evolving requirements into working software, delivering high-quality iterations with limited upfront specifications. Collaborate with engineering teams: Partner with engineering managers and fellow developers to maintain strong standards for architecture, code quality, testing, documentation, and maintainability. 3. Core Qualifications 6+ years of professional software engineering experience building and shipping production systems at established technology organizations or comparable environments. Strong hands-on production expertise in at least one of Python, Java, Rust, C#, or C++, along with meaningful professional experience delivering software in a second programming language or ecosystem. Demonstrated full-stack engineering experience covering: Backend services and API development Modern frontend frameworks such as React or equivalent Database and data-model design Cloud infrastructure and deployment Production operations and system reliability Experience owning software systems end to end, from design and implementation through deployment, monitoring, debugging, and ongoing improvement. Ability to quickly understand unfamiliar architectures, repositories, development environments, and technical requirements, then begin delivering production-quality code with minimal ramp-up. Demonstrated career progression and increasing technical ownership throughout your engineering career. Strong understanding of software engineering best practices, including testing, version control, code review, debugging, system design, and technical documentation. Experience working with AI/ML systems, LLM APIs, AI coding tools, or model evaluation workflows is advantageous. Strong written and verbal communication skills, with the ability to clearly explain technical decisions, trade-offs, implementation details, and system behavior. Ability to commit reliably to 40 hours per week during weekdays. 4. What Success Looks Like The successful candidate will be able to quickly become productive within unfamiliar technical environments, independently solve complex engineering problems, and deliver reliable software that helps teams evaluate and advance frontier AI capabilities. You should be comfortable operating in a fast-moving environment where requirements evolve quickly, technical ambiguity is common, and high-quality working code is valued over lengthy upfront planning. 5. Equal Opportunity We are committed to providing equal employment opportunities to all qualified applicants. We do not discriminate based on legally protected characteristics and provide reasonable accommodations to qualified individuals throughout the application and engagement process. 6. Role Details Role: Senior Software Engineer, Full Stack Specializations: Python, Java, Rust, C#, C++, TypeScript Employment Type: Full-Time Work Commitment: 40 hours per week Focus: Full-stack development, AI model integration, software evaluation, testing, debugging, and production engineering

Translate design specifications into pixel-perfect web interfaces and improve AI-driven frontend engineering models. | 3+ years frontend experience with strong TypeScript, CSS3, HTML skills, building responsive accessible interfaces, and remote work capability. | This role is for one of our clients $40 - $50/hourpay Role Title: Frontend Software Engineer Role Type: Contractor Location: Remote We are seeking experienced Frontend Software Engineers to contribute to an AI-driven initiative focused on building and evaluating high-quality user interfaces. In this role, you will apply your frontend development expertise to help improve next-generation AI systems by creating accurate, production-quality UI implementations and providing domain-specific technical insights. No prior AI experience is required. Your knowledge of frontend engineering, responsive design, and modern web technologies will play a key role in helping AI models learn how to build visually polished, accessible, and high-performing web applications. Key Responsibilities Translate detailed component specifications, design systems, and UI mockups into accurate, production-quality web interfaces. Build pixel-perfect, responsive user interface components using TypeScript, CSS3, and modern frontend development practices. Ensure all implementations follow established design systems, accessibility standards, and responsive design principles. Collaborate effectively within a remote-first environment through clear technical documentation, code reviews, and constructive feedback. Identify and resolve inconsistencies or ambiguities in design specifications before implementation. Optimize frontend performance to deliver fast-loading, responsive, and seamless user experiences across browsers and devices. Contribute technical expertise to support the development and evaluation of advanced AI models for frontend engineering tasks. Required Qualifications 3+ years of professional experience in frontend software development. Strong proficiency in TypeScript, CSS3, HTML, and modern responsive web development. Demonstrated experience building pixel-perfect interfaces from design specifications, mockups, or screenshots. Experience working with component libraries, design systems, and reusable UI architectures. Strong understanding of responsive layouts, cross-browser compatibility, accessibility (WCAG), and frontend performance optimization. Excellent written and verbal communication skills in English. Self-motivated with the ability to work independently in distributed, remote development environments. Preferred Qualifications Experience extending or maintaining enterprise design systems. Familiarity with modern frontend frameworks and component-driven development. Strong eye for visual detail and UI consistency. Experience collaborating with designers and cross-functional engineering teams. Master's degree or PhD in Computer Science, Software Engineering, or a related technical discipline is a plus. Engagement Details Fully remote opportunity with flexible working arrangements. Collaborate with multidisciplinary teams on advanced AI and frontend engineering projects. Apply real-world frontend development expertise to improve AI-generated user interfaces and engineering workflows. Opportunities for continued engagement based on project needs and performance. Equal Opportunity We are committed to providing equal opportunities to all qualified applicants and offer reasonable accommodations throughout the application and engagement process upon request.

Review and validate logistics documentation and workflows to improve AI-driven supply chain systems. | 3+ years logistics or supply chain experience with shipping documentation expertise and strong analytical and communication skills. | This role is for one of our clients $40 - $50/hourpay Role Title: Logistics & Supply Chain Management Specialist Role Type: Contractor Location: Remote We are seeking experienced Logistics & Supply Chain Management Specialists to contribute their expertise to an AI-driven project focused on optimizing supply chain operations, documentation, and business workflows. In this role, you will help improve next-generation AI systems by providing high-quality, real-world insights into logistics processes and industry-standard documentation. No prior experience in artificial intelligence is required. Your expertise in logistics, supply chain operations, and global trade documentation will play a critical role in developing more accurate and reliable AI models. Key Responsibilities Review, analyze, and validate logistics documents, including packing lists, bills of lading, inventory registers, and related shipping documentation for accuracy, completeness, and industry compliance. Create and annotate sample logistics documents that demonstrate best practices in supply chain management and operational excellence. Evaluate existing supply chain workflows and recommend practical process improvements based on real-world industry experience. Provide structured feedback on logistics scenarios, emphasizing document quality, workflow efficiency, and operational accuracy. Collaborate with cross-functional project teams to clarify logistics concepts and communicate complex supply chain processes clearly and effectively. Participate in quality assurance activities by reviewing and validating logistics datasets used for AI training and evaluation. Contribute to the development of reference materials, documentation standards, and training resources that reflect modern supply chain operations and industry best practices. Required Qualifications 3+ years of professional experience in logistics, supply chain management, freight operations, procurement, or related fields. Hands-on experience working with logistics documentation such as: Packing Lists Bills of Lading (BOL) Inventory Registers Shipping and transportation documentation Strong understanding of global logistics operations, inventory management, freight movement, and supply chain workflows. Excellent analytical and problem-solving abilities with experience identifying operational improvements. Strong written and verbal communication skills in English. High attention to detail with the ability to review complex documentation accurately. Ability to work independently in a remote, collaborative environment while meeting project deadlines. Preferred Qualifications Master's degree in Supply Chain Management, Logistics, Operations Management, or a related discipline. Experience improving logistics processes or implementing operational efficiencies. Familiarity with international shipping standards, inventory control systems, and supply chain documentation practices. Experience contributing to documentation, training materials, or process standardization initiatives. Engagement Details Fully remote opportunity with flexible working arrangements. Collaborate with multidisciplinary teams on AI-focused logistics and supply chain projects. Opportunity to apply real-world logistics expertise to improve advanced AI systems. Long-term engagement opportunities may be available based on project requirements and performance. Equal Opportunity We are committed to providing equal opportunities to all qualified applicants and offer reasonable accommodations throughout the application and engagement process upon request.