Evaluate and author high-quality computer science content to improve AI model reasoning and accuracy. Analyze complex CS problems, create scenarios/datasets, review AI outputs for correctness, and collaborate remotely to refine guidelines and documentation.
This role is for one of our clients
$20 - $40/hourpay
Role Title: Computer Science Subject Matter Expert (AI Training)
Role Type: Contractor
Location: Remote
We are seeking a Computer Science Subject Matter Expert to contribute to the development of next-generation AI systems by applying deep technical expertise to real-world computer science challenges. In this role, you will analyze, evaluate, and create high-quality technical content that enhances the reasoning, accuracy, and performance of AI models. Prior experience in Artificial Intelligence is not required—your expertise in Computer Science is the primary qualification.
RequirementsKey ResponsibilitiesTechnical Analysis & Problem Solving
- Analyze and evaluate complex computer science problems, solutions, and methodologies across various domains.
- Assess technical approaches and recommend well-structured, scalable, and efficient solutions based on industry best practices.
- Ensure technical accuracy, logical consistency, and clarity in all deliverables.
- Author, review, and refine technical documentation, including system design documents, research papers, technical specifications, and architecture write-ups.
- Develop real-world computer science scenarios, datasets, and case studies to support AI model training and evaluation.
- Create structured technical explanations that improve AI understanding and reasoning.
- Review AI-generated responses for technical correctness, completeness, and adherence to computer science principles.
- Identify inaccuracies, inconsistencies, and opportunities for improvement while providing constructive feedback.
- Support the evaluation and continuous enhancement of AI-driven tools through domain expertise.
- Work closely with project coordinators and subject matter experts to refine task guidelines and improve data quality.
- Provide clear written and verbal feedback to enhance AI model relevance, robustness, and performance.
- Collaborate in a remote environment while maintaining high-quality deliverables and documentation.
- Bachelor's, Master's, or PhD in Computer Science or a related field.
- Strong understanding of core computer science concepts, including algorithms, data structures, operating systems, databases, networking, and software engineering.
- Experience writing technical documentation, research papers, system design documents, or technical reports.
- Excellent analytical, problem-solving, and critical thinking skills.
- Strong written and verbal communication skills with the ability to explain complex technical concepts clearly.
- Ability to work independently and deliver high-quality work in a remote environment.
- Expertise in one or more specialized domains such as:
- Algorithms & Data Structures
- Distributed Systems
- Computer Networks
- Databases
- Artificial Intelligence & Machine Learning
- Cloud Computing
- Cybersecurity
- Experience participating in technical reviews, research projects, or open-source contributions.
- Proven ability to simplify complex technical concepts for both technical and non-technical audiences.
- Familiarity with current trends and emerging technologies in computer science.
- Computer Science
- Algorithms & Data Structures
- System Design
- Technical Documentation
- Problem Solving
- Distributed Systems
- Databases
- Networking
- Artificial Intelligence
- Research & Publications
- Open Source Contributions
- Software Engineering
- Technical Reviews
Similar Jobs
Aerospace • Artificial Intelligence • Cloud • Machine Learning • Software • Cybersecurity • Defense
Conduct third-party due diligence and compliance screenings, coordinate escalations, monitor screening systems, and ensure adherence to laws and company policies. The role also develops ethics and compliance training, collaborates cross-functionally, and drives data analytics and insights for the Third Party Risk and Digital Compliance team.
AdTech • Big Data • Digital Media • Software
Designs and reviews security architecture, performs threat modeling and cloud assessments, responds to incidents, manages security tools, and advises engineering teams on secure development. Conducts code and vulnerability reviews using OWASP and MITRE ATLAS, evaluates AI and LLM security risks, and supports security monitoring, risk assessment, data protection, and compliance across applications, infrastructure, and endpoints.
Top Skills:
AWSC++DastGoogle SecopsHmacIso 27001IspmJavaLinuxmacOSMitre AtlasNist CsfOauthOwaspOwasp Top 10 For LlmsPythonSAMLSastScalaSoc 1Soc 2SoxSplunkTenable CloudWazuhWindows
Fintech • Legal Tech • Software • Financial Services • Cybersecurity • Data Privacy
Leads the architecture, design, deployment, and operation of enterprise middleware messaging and streaming integrations. Designs multi-region, multi-datacenter platforms with geo-replication, failover, high availability, fault tolerance, and low-latency performance. Evaluates messaging technologies, establishes deployment and monitoring standards, automates infrastructure, collaborates with stakeholders, and mentors junior engineers. The role requires extensive experience with Kafka, RabbitMQ, cloud messaging services, Kubernetes, Docker, clustered environments, and resilient high-volume systems.
Top Skills:
ActivemqApache KafkaAws SnsAws SqsAzure Service BusDockerElasticGcp Pub/SubIbm MqKafka StreamsKubernetesRabbitMQRedpandaStreamnative
What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine



