10a Labs

• Proactively detect and reacquire bad actors on our platform. • Investigate potentially policy-violating activity by querying internal data sources (using SQL and Python) and cross-referencing open source information (OSINT). • Document and share investigative findings with internal stakeholders.

Role Description 10a Labs' Investigations Team is looking for a Principal Cyber Investigator to lead day-to-day operations and oversee quality across a cyber investigations team. This role requires senior cybersecurity expertise combined with the operational and leadership experience to manage a high-performing team, interface directly with client stakeholders, and set the standard for investigative and labeling output quality and consistency. In this role, you will: - Oversee day-to-day operations of the cyber investigations team, ensuring investigations are completed accurately, efficiently, and in accordance with outlined requirements and rubrics. - Serve as the senior technical authority on complex and escalated cases, making final determinations on real-world harm potential and offensive uplift. - Monitor and maintain quality metrics across the team, identifying gaps and implementing improvements to investigative processes and detection pipelines. - Interface directly with client stakeholders to communicate findings, surface emerging trends, and align on evolving policy and operational priorities. - Mentor and develop senior and junior investigators, providing guidance on technically demanding and ambiguous cases. - Lead threat actor analysis, synthesizing findings across cases to inform broader detection and mitigation strategies. - Query internal data sources via DQL and programmatically, and cross-reference open-source information (OSINT) to support investigations and validate team output. - Respond to critical escalations and on-call leads, including those not caught by existing safety systems. Qualifications - At least 9+ years of experience in cybersecurity, threat intelligence, Trust & Safety, national security, defense, intelligence, or law enforcement domains. - Bachelor's degree in Computer Science, Information Security, or a related field, or equivalent practical experience. - Demonstrated experience leading or managing investigative teams, including oversight of quality, output, and team development. - Deep subject-matter expertise in one or more of the following: scaled data extraction, ransomware, local and remote exploits, or offensive security operations. - Familiarity with LLM systems and how AI technology can be misused for cyber operations. - Proven ability to serve as a final technical authority on complex cases, with a track record of sound judgment on harm potential and offensive uplift. - Strong SQL, Python, and other data language proficiency for querying data, supporting detection workflows, and validating investigative output. - Exceptional written and verbal communication skills, with experience presenting findings to senior stakeholders. - Ability to rapidly context-switch across domains, modalities, and abuse areas in a fast-paced, ambiguous environment. - Ability to clear an insider-threat background check. Preferred Qualifications - Experience working directly with or within frontier AI labs, large technology platforms, or Trust & Safety organizations. - Experience with threat intelligence frameworks such as MITRE ATT&CK. - Background in dark web monitoring, OSINT, or cross-platform threat analysis. - Experience building or scaling detection and mitigation pipelines. - Full professional proficiency in Arabic, Chinese, Farsi, Portuguese, Russian, or Spanish. - Active security clearance (Secret or above). - Relevant certifications such as OSCP, GREM, or GCTI. Benefits - Salary Range: $150K–$180K, depending on experience and location. - Work Environment: Fully remote, U.S.-based. - Health Benefits: Comprehensive health, dental, and vision coverage. - Time Off: Generous PTO and paid holiday schedule. - Retirement: 401(k) plan.

Role Description 10a Labs' Investigations Team is looking for a Senior Cyber Investigator to support critical safety incidents and conduct investigations across a range of cyber abuse areas. This role requires deep cybersecurity subject-matter expertise to detect and respond to malicious activity, assess threat actor behavior at the organizational level, and handle escalated cases requiring senior technical judgment. Investigations may involve exposure to harmful or disturbing content, including malicious code, exploit development, and content designed to facilitate cyberattacks. - Detect and investigate malicious uses and cyber abuse, including cases involving scaled data extraction, ransomware, and local and remote exploits. - Conduct org-level analysis of threat actor behavior, identifying patterns across cases to inform detection and mitigation strategies. - Handle escalated and technically complex cases, applying senior cybersecurity expertise to assess real-world harm potential. - Query internal data sources using SQL and Python and cross-reference open-source information (OSINT) to support investigations. - Document and share investigative findings and recommendations with internal stakeholders and client teams. - Support quality and consistency across the investigations team, providing guidance to junior investigators on ambiguous cases. - Respond to reactive escalations and on-call leads, including those not caught by existing safety systems. Qualifications - At least 5+ years of experience in cybersecurity, threat intelligence, Trust & Safety, national security, defense, intelligence, or law enforcement domains. - Bachelor's degree in Computer Science, Information Security, or a related field, or equivalent practical experience. - Familiarity with LLM systems and how AI technology can be misused for cyber operations. - Deep subject-matter expertise in one or more of the following: scaled data extraction, ransomware, local and remote exploits, or offensive security operations. - Strong ability to assess the real-world harm potential of technical content, distinguishing genuine offensive uplift from benign or educational security research. - Strong SQL and Python proficiency for querying data and supporting detection workflows. - Proven experience conducting org-level threat actor analysis across large datasets. - Ability to rapidly context-switch across domains, modalities, and abuse areas in a fast-paced, ambiguous environment. - Ability to clear an insider-threat background check. Preferred Qualifications - Experience with threat intelligence frameworks such as MITRE ATT&CK. - Background in dark web monitoring, OSINT, or cross-platform threat analysis. - Experience scaling and automating detection and mitigation processes. - Full professional proficiency in Arabic, Chinese, Farsi, Portuguese, Russian, or Spanish. - Relevant certifications such as OSCP, GREM, or GCTI. Benefits - Salary Range: $115K–$140K, depending on experience and location. - Work Environment: Fully remote, U.S.-based. - Health Benefits: Comprehensive health, dental, and vision coverage. - Time Off: Generous PTO and paid holiday schedule. - Retirement: 401(k) plan.

Role Description 10a Labs' Investigations Team is looking for a Cyber Investigator to support high-volume exchange labeling and investigations across a range of cyber abuse areas. This role requires a solid foundation in cybersecurity and a keen ability to assess whether technical content poses real-world harm. Investigations may involve exposure to harmful or disturbing content, including malicious code, exploit development, and content designed to facilitate cyberattacks. In this role, you will: - Review and label AI-generated exchanges to assess whether content provides meaningful offensive cyber uplift, distinguishing it from legitimate security research. - Investigate potentially policy-violating activity by querying internal data sources using SQL and Python and cross-referencing open-source information (OSINT). - Document and share investigative findings with internal stakeholders. - Respond to reactive escalations and on-call leads, including those not caught by existing safety systems. Qualifications - At least 1–3 years of experience in cybersecurity, Trust & Safety, national security, defense, intelligence, or law enforcement domains. - Bachelor's degree in Computer Science, Information Security, or a related field, or equivalent practical experience. - Foundational knowledge of cyber threat concepts, including one or more of the following: scaled data extraction, ransomware, local and remote exploits, or offensive security operations. - Familiarity with LLM systems and how AI technology can be misused for cyber operations. - Ability to assess the real-world harm potential of technical content, distinguishing offensive uplift from benign or educational security research. - Strong SQL and Python proficiency for querying data and supporting investigations. - Ability to rapidly context-switch across domains, modalities, and abuse areas in a fast-paced, ambiguous environment. - Ability to clear an insider-threat background check. Requirements - Experience with threat intelligence frameworks such as MITRE ATT&CK. - Background in dark web monitoring, OSINT, or cross-platform threat analysis. - Full professional proficiency in Arabic, Chinese, Farsi, Portuguese, Russian, or Spanish. - Relevant certifications such as CompTIA Security+, CEH, or OSCP. Benefits - Salary Range: $80K–$105K, depending on experience and location. - Work Environment: Fully remote, U.S.-based. - Health Benefits: Comprehensive health, dental, and vision coverage. - Time Off: Generous PTO and paid holiday schedule. - Retirement: 401(k) plan.

Role Description As a Red Teaming Fellow, you will help evaluate the safety, security, and reliability of advanced AI systems. Fellows work alongside researchers, engineers, and subject-matter experts to identify vulnerabilities, uncover failure modes, and generate insights that help organizations deploy AI systems more safely. This is a hands-on fellowship at the intersection of AI, security, and adversarial testing. Fellows will contribute to real-world evaluations of frontier models and AI-enabled systems, helping design and execute tests that probe how models behave under challenging or unexpected conditions. - Conduct adversarial testing of AI systems across safety, security, and misuse scenarios - Design and execute red teaming exercises against models, agents, and AI-enabled applications - Develop prompts, attack strategies, and test cases to identify vulnerabilities and failure modes - Analyze model behavior and document findings in clear, actionable reports - Support the development of evaluation frameworks, taxonomies, and testing methodologies - Research emerging AI threats, attack techniques, and risk trends - Collaborate with engineers, researchers, and subject-matter experts to investigate emerging risks and threat vectors - Develop front-end dashboards and other visualizations Qualifications - Pursuing or recently completed a degree in Computer Science, Cybersecurity, Engineering, Data Science, Mathematics, Political Science, International Relations, or a related field - Strong interest in AI safety, cybersecurity, red teaming, or adversarial testing - Familiarity with AI abuse including jailbreaking, system prompt extraction, indirect prompt injection, data exfiltration, etc. - Strong analytical, research, problem-solving, and communication skills - Ability to think creatively from an adversarial perspective - Ability to work independently and collaboratively in a remote environment - Experience with Python, Bash, large language models, AI systems, cybersecurity, or research methodologies preferred - Proficiency in a language other than English preferred Benefits - Flexible start / end dates - Remote work (based in the continental U.S.) - Flexible schedule, up to 20 hours per week (negotiable) - Hourly pay commensurate with experience and qualifications - $25 per hour for undergraduate students - $32.50 per hour for graduate students

Role Description We are seeking a Machine Learning Engineer (3–5+ years of experience) to help design, build, evaluate, and deploy advanced machine learning systems across a range of safety, security, and intelligence applications. This role spans the full ML lifecycle, from dataset development and experimentation to model training, evaluation, deployment, and monitoring. You will work both independently and collaboratively across projects involving multimodal classification systems, frontier model evaluations, model distillation research, and agentic workflows. The ideal candidate combines strong engineering fundamentals with a research mindset and enjoys tackling ambiguous, high-impact problems at the frontier of AI. You will collaborate closely with researchers, software engineers, red teamers, and subject-matter experts to develop production-ready systems that support leading AI organizations and technology companies. - Design, train, evaluate, and deploy machine learning models across text, image, audio, and multimodal domains. - Develop and improve classification systems for safety, security, abuse detection, and intelligence applications. - Conduct experiments to benchmark, evaluate, and compare AI models, including large language models and multimodal systems. - Contribute to model distillation, optimization, and fine-tuning efforts to improve performance, efficiency, and deployability. - Design evaluation pipelines, metrics, and testing frameworks to measure model capabilities, reliability, and safety. - Build agentic systems and automated workflows for evaluation, red teaming, research, and large-scale experimentation. - Own ML projects from initial research and prototyping through production deployment and monitoring. - Partner with software engineers to productionize ML systems and support ongoing improvements. - Provide technical expertise and guidance across client engagements and internal research initiatives. Qualifications - Brings curiosity, creativity, and rigor to ambiguous research and engineering problems, with a bias toward experimentation and rapid iteration. - Thrives in collaborative, interdisciplinary environments while also being comfortable independently driving projects to completion. - Communicates technical concepts clearly to both technical and non-technical audiences. - Is resourceful, proactive, and comfortable operating in a fast-moving startup environment. - Is excited about developing novel approaches that advance the state of AI safety, evaluation, and security. Requirements - 3–5+ years of professional experience building and deploying machine learning systems. - Strong proficiency in Python and modern machine learning frameworks such as PyTorch and/or TensorFlow. - Experience working across multiple modalities, with expertise in one or more of: - Computer Vision: image classification, object detection, OCR, segmentation, deepfake detection, multimodal vision-language systems, or related areas. - Natural Language Processing: LLMs, text classification, information extraction, retrieval systems, speech-to-text, agentic applications, or related areas. - Experience training, fine-tuning, evaluating, and deploying machine learning models in production environments. - Experience designing evaluation methodologies, benchmarking systems, and model performance metrics. - Experience with MLOps tools and practices (Docker, Kubernetes, CI/CD for ML, MLflow, etc.). - Experience with cloud platforms such as Google Cloud Platform (preferred), AWS, or Azure, including ML infrastructure, workflow orchestration, storage, and database services. - Familiarity or experience with model distillation, synthetic data generation, reinforcement learning, or AI evaluation research is strongly preferred. Benefits - Salary Range: $130K–$200K, depending on experience and location. - Bonus: Performance-based annual bonus. - Professional Development: Support for conferences, continuing education, or leadership training. - Work Environment: Fully remote, U.S.-based. - Health Benefits: Comprehensive health, dental, and vision coverage. - Time Off: Generous PTO and paid holiday schedule.

Role Description We are seeking an AI Red Teamer with deep cybersecurity expertise to help evaluate the security and resilience of advanced AI systems and applications. This role is ideal for someone who enjoys offensive security, creative problem-solving, and thinking like an adversary. - Design and execute red team assessments against AI systems, applications, and supporting infrastructure - Translate ambiguous objectives into structured testing plans and attack strategies - Develop adversarial testing methodologies to evaluate system security, robustness, and resilience - Craft prompts, attack chains, and adversarial inputs to uncover unintended or unsafe system behavior - Identify vulnerabilities, security risks, and failure modes through testing and analysis - Analyze system outputs and behaviors to assess security and safety risks - Document findings, communicate risk, and provide actionable recommendations - Collaborate with engineers, researchers, and subject-matter experts to improve system security - Continuously refine testing methodologies based on emerging threats and attacker techniques Qualifications - Degree in Computer Science, Engineering, Cyber Security, or a related field (or equivalent practical experience) - Strong understanding of cybersecurity principles, attack methodologies, and common vulnerability classes - Experience with security tools such as Splunk, Wireshark, Metasploit, Burp Suite, Nmap, or similar platforms - Comfortable working in Linux and terminal-based environments - Experience scripting or automating workflows using Python, Bash, or similar languages - Familiarity with SIEM platforms and security monitoring concepts - Ability to think creatively from an adversarial perspective and investigate complex technical problems - Excellent analytical and problem-solving skills - Excellent written and verbal communication skills Requirements - CompTIA Security+ certification and/or Google Cybersecurity Certificate - Experience testing AI, machine learning, or large language model applications - Familiarity with prompt injection, jailbreak techniques, or other AI attack methodologies - Offensive security certifications such as PNPT, OSCP, CySA+, GCIH, or GPEN - Experience supporting government, defense, intelligence, or critical infrastructure environments Benefits - Salary Range: $100K–$120K, depending on experience and location - Bonus: Performance-based annual bonus - Professional Development: Support for conferences, continuing education, or leadership training - Work Environment: Fully remote, U.S.-based - Health Benefits: Comprehensive health, dental, and vision coverage - Time Off: Generous PTO and paid holiday schedule - Retirement: 401(k) plan

About 10a Labs: 10a Labs is the safety and threat-intelligence layer trusted by frontier AI labs, AI unicorns, Fortune 10 companies, and leading global technology platforms. Our adversarial red teaming, model evaluations, and intelligence collection enable engineering, safety, and security teams to stay ahead of evolving threats and deploy AI systems safely. Data Center Watch is a research project that tracks political risks emerging from local opposition to data centers with the aim of understanding the emerging regulatory landscape of data center development in the U.S. In this role, you will: - Conduct open-source and targeted research in various sources, including social media, forums, and news outlets - Analyze, summarize, and clearly report findings for a variety of stakeholders - Explore emerging questions and pursue lines of inquiry as they arise, adjusting focus as priorities shift - Collaborate with teammates to design and refine research methods or analytic approaches - Draft reports, prepare presentation materials, and support podcast development - Work on sensitive topics with professionalism, balance, and care - Support other critical initiatives as needed We're looking for someone who: - Is passionate about critical infrastructure, AI, data centers, and the social dimension of technology - Possesses strong analytical, writing, and research skills - Has experience or coursework in local politics, public opinion research, international studies, data centers, or related fields - Thinks critically, communicates findings clearly, and adapts quickly to evolving tasks Requirements: - Bachelor's degree in international relations, political science, economics, human geography, or a related field — or equivalent professional experience - Demonstrated interest or experience in online research, information security, or trust & safety - Ability to quickly summarize complex information into concise, actionable reports - Comfort working independently and collaboratively in a remote setting - Exceptional verbal and written communication skills - Data visualization skills, slide presentation, and basic scripting skills (e.g., Python) or familiarity with research automation tools Compensation & Benefits: - Remote work (based in the continental U.S.) - Flexible schedule, up to 20 hours per week (negotiable) - $25 per hour for undergraduate students - $32.50 per hour for graduate students

About 10a Labs: 10a Labs is the safety and threat-intelligence layer trusted by frontier AI labs, AI unicorns, Fortune 10 companies, and leading global technology platforms. Our adversarial red teaming, model evaluations, and intelligence collection enable engineering, safety, and security teams to stay ahead of evolving threats and deploy AI systems safely. 3–8 Years of Industry Experience | Remote | High-Impact About the Role: We’re looking for an infrastructure-focused engineer who thrives at the intersection of machine learning, systems, and product delivery. This is a hands-on role responsible for deploying, monitoring, and scaling a real-time ML-powered content moderation system used to detect and triage abuse, threats, and edge-case language. You’ll work closely with ML engineers, researchers, and clients to build infrastructure that makes high-performance models accessible and reliable in the wild. In This Role, You Will: - Design and maintain cloud infrastructure (GCP or AWS) to support real-time model serving, data ingestion, and evaluation workflows. - Deploy and optimize APIs for low-latency access to ML models and embedding search systems. - Manage and optimize the end-to-end training data flow—from sourcing and cleaning datasets to preparing them for model consumption—ensuring accuracy, scalability, and efficiency. - Build observability tooling for production ML pipelines (monitor latency, error rates, request volumes, drift). - Automate model deployment, retraining, and evaluation pipelines (CI/CD for ML). - Work with ML engineers to package models for serving. - Help manage vector databases and semantic search infrastructure (e.g., Pinecone, FAISS, Vertex Matching Engine). - Ensure security, compliance, and uptime of infrastructure supporting safety-critical systems. We’re Looking for Someone Who: - Has 3–8 years of experience deploying machine learning systems or high-availability backend systems. - Has shipped and maintained production infrastructure at scale, supporting ML workflows. - Has experience with GCP, AWS, or similar platforms (including managed ML services). - Is proficient in Terraform, Docker, Kubernetes, or similar infra tools. - Understands performance tradeoffs in serving models and embedding search pipelines. - Can work cross-functionally with ML, security, and product teams to deploy safely and iterate fast. - Brings a builder's mindset and bias for ownership in ambiguous environments. Nice to Have Experience With: - Experience with vector databases or ANN systems, preferably within GCP (or AWS). - Experience serving LLMs or embedding-based models via API. - Experience with model monitoring, logging, and metrics platforms (e.g., Prometheus, Grafana, Sentry). - Familiarity with trust & safety infrastructure, abuse detection, or policy enforcement systems. What Success Looks Like in the First 3 Months: - You’ve deployed and monitored a real-time ML inference system with well-defined observability. - You’ve implemented an API with latency under 200ms for embedding or classifier-based inference. - You’ve partnered with ML engineers to streamline deployment and retraining workflows. - You’ve built logging and monitoring that gives insight into system performance and classifier behavior. Compensation & Benefits: - Salary Range: $130K–$230K, depending on experience and location. - Bonus: Performance-based annual bonus. - Professional Development: Support for continuing education, conferences, or training. - Work Environment: Fully remote, U.S.-based. - Health Benefits: Comprehensive health, dental, and vision coverage. - Time Off: Generous PTO and paid holiday schedule. - Retirement: 401(k) plan.

About 10a Labs: 10a Labs is the safety and threat-intelligence layer trusted by frontier AI labs, AI unicorns, Fortune 10 companies, and leading global technology platforms. Our adversarial red teaming, model evaluations, and intelligence collection enable engineering, safety, and security teams to stay ahead of evolving threats and deploy AI systems safely. About 10a Labs: 10a Labs is the safety and threat-intelligence layer trusted by frontier AI labs, AI unicorns, Fortune 10 companies, and leading global technology platforms. Our adversarial red teaming, model evaluations, and intelligence collection enable engineering, safety, and security teams to stay ahead of evolving threats and deploy AI systems safely. In this role, you will: - Design, implement, and optimize end-to-end data pipelines for scraping and processing structured and unstructured data using Google Cloud Platform (or similar) and best practices; - Conduct ad hoc web scraping and data collection to support research and intelligence initiatives; - Prepare data for further analysis, including data cleaning, transformation, anonymization, and masking; - Contribute to the development of internal and external APIs, following best practices; - Collaborate with ML engineers, other data engineers, and software developers to deliver actionable insights and functional tools, including internal and external dashboards, APIs, and data dumps; and - Drive other critical initiatives. Requirements: - Degree (or equivalent work experience) in Computer Science, Engineering, Information Science, Data Science or a related field (graduate degree preferred) - 2+ years of professional experience in data engineering or a closely related field - Ability to communicate complex technical ideas clearly to non-technical audiences - Proficiency in Python, SQL - Experience with web scraping/crawling (e.g., Beautiful Soup, Selenium, Scrapy) - Experience with Google Cloud Platform (or similar), including storage and database services (e.g., Cloud Storage, CloudSQL, Cloud Spanner) and workflow orchestration (e.g., Cloud Composer/Airflow, Cloud Run, Pub/Sub) - Experience building and managing data pipelines, especially for text data - Comfort working in fast-moving, high-impact environments, such as startups, AI research labs, or security-focused teams Compensation & Benefits: - Salary Range: $105K–$125K, depending on experience and location - Bonus: Performance-based annual bonus - Professional Development: Support for conferences, continuing education, or leadership training - Work Environment: Fully remote, U.S.-based - Health Benefits: Comprehensive health, dental, and vision coverage - Time Off: Generous PTO and paid holiday schedule Retirement: 401(k) plan