Role Description The Data team is the engine of intelligence at OfferUp. Our mission is to transform massive amounts of marketplace data into seamless, safe, and personalized experiences that empower millions of people to connect and prosper. We bridge the gap between complex algorithms and real-world customer impact across search, trust & safety, and personalization. AI is transforming how millions of people buy, sell, and connect on OfferUp - and this role is at the center of making that happen. As an AI Engineer on the Data team, you will own the production systems — from agentic workflows and RAG pipelines to LLM integrations - that turn our marketplace intelligence into real customer experiences. Your work will have a company-wide impact and be felt by millions of users every day. We are looking for an AI Engineer to join our Data team. This team is tasked with building the core intelligence that is critical to OfferUp's success as the leading local marketplace. - Breadth of Impact: You won't be siloed; you will build AI systems that drive results across Search & Discovery, Trust & Safety, Advertising, and core Personalization. - Modern AI Stack: Work with agentic frameworks (LangChain, LangGraph), RAG architectures, and LLM APIs to solve real marketplace problems. - Production Ownership: You will build, ship, and own AI features end-to-end, from design through deployment. - Collaborative Environment: Work alongside Senior Data Scientists and Engineers, positioning you at the intersection of research and production. In this role, you will: - Design and build agentic AI systems and RAG pipelines for production features across the marketplace. - Integrate LLMs into product experiences across search, categorization, communication, and trust & safety. - Partner with Data Scientists and Engineers to turn research into shipped products. Here’s more of what you will get to do: - Impact on Product: Deliver the next generation of Search, Personalization, and Trust & Safety features powered by reliable, production-quality AI systems. - Impact on Company: Directly contribute to key business KPIs (conversion, retention, fraud reduction) by turning data science insights into shipped capabilities. - Critical Projects: Production RAG pipelines for intelligent discovery; agentic workflows for marketplace automation; tooling and infrastructure for rapid, safe LLM deployment. Qualifications - 2-4 years building and deploying AI/ML systems in production. - 2+ years professional Python development. - Hands-on experience with agentic frameworks (LangChain, LangGraph, or similar) including function calling and tool-use design. - Practical experience building RAG systems (vector search, semantic chunking, rerankers). - Experience with LLM APIs, prompt engineering, and structured outputs. - Proficiency with async Python (asyncio, streaming) and Pydantic. - Strong SQL skills for large-scale data systems. - Bachelor's in CS, Math, Statistics, or related field (or equivalent experience). - Collaborative mindset and strong communication skills. Requirements - Helpful, but not required: LLMOps tooling: evals (Ragas, DeepEval), observability (LangSmith, Arize Phoenix), guardrails (NeMo). - Cloud deployment of AI services (AWS preferred). - GraphRAG or knowledge graph integration (Neo4j/FalkorDB). - ReAct, Plan-and-Solve, or multi-agent collaboration patterns. Benefits - Compensation Range: $140,000 - $160,000. - Health insurance, healthcare savings and spending accounts. - Retirement savings benefits (401(k) plan with match). - Basic and voluntary life insurance. - Disability benefits. - Paid time off for sick leave, family and/or medical leave, vacation, and 12 company holidays. - Flexible vacation policy, generally expected to take 3-5 weeks of pre-planned vacation time per year. - 12 days (96 hours) of sick time per year (pro-rated if the start date is other than January 1).

Paper is reimagining how schools support students so that every learner can reach their full potential. Our vision is a world where every student receives timely, personalized, and relevant academic support. We offer a suite of scalable solutions including 24/7 tutoring, writing feedback, math practice, college and career support, and AI-powered instructional tools that provide personalized support to all students, including multilingual learners. Our GROW high-impact tutoring program accelerates learning through targeted small-group instruction, delivers measurable gains in student achievement, and eases teacher workloads. Trusted by 500+ school districts across 40+ states and backed by leading investors including IVP, Sapphire Ventures, Framework Capital, and Reach Capital, we’re pursuing a bold goal: to drive the best academic outcomes for as many students as possible. Recent articles: - GROW by Paper Drives 201% Increase in Grade-Level Proficiency in Just 12 Weeks - GROW by Paper Earns Stanford’s NSSA Tutoring Program Design Badge, Signaling Excellence in Research-Aligned Design - Paper Appoints Marisa Burkhart as CRO Job Description About the Role We are building the first B2B, in-classroom Voice + Video AI Tutor designed for real-world learning environments. Our system operates in live classrooms—processing noisy audio, interpreting visual signals, and delivering low-latency, safe, pedagogically aligned AI support to educators and students. We are seeking a Senior AI / Machine Learning Manager to lead a team of 3–5 ML engineers and data scientists building multimodal AI systems that power critical product features across our platform. This team develops trained models, generative AI systems, and agentic learning assistants that support millions of learners and educators. You will be responsible for defining the technical direction, mentoring the team, and delivering production-ready AI capabilities that operate reliably in complex real-world environments. This is a high-impact role with significant technical ownership, shaping how AI is embedded into our platform—from early research and experimentation through deployment and continuous optimization. You will work closely with Product, Data, Platform, and Engineering leaders to bring cutting-edge AI capabilities into classrooms at scale. Key Responsibilities Technical Leadership - Lead the design, development, and deployment of AI-powered product features, including trained models, generative AI systems, and agentic learning assistants. - Architect systems that support real-time multimodal AI, integrating signals from audio, video, and text to support classroom interactions. - Guide architecture decisions for LLM orchestration, prompt frameworks, retrieval systems, and agent-based workflows. - Ensure AI systems meet strict requirements for latency, safety, and reliability in live classroom environments. - Establish best practices for model development, evaluation, monitoring, and MLOps. Agentic Learning Systems - Design and implement agentic AI systems that guide, coach, and teach students through interactive learning experiences. - Build AI capabilities that support adaptive instruction, classroom assistance, and educator workflows. - Develop safe, pedagogically aligned AI interactions appropriate for real-world classroom use. Team Leadership - Manage and mentor a team of 3–5 ML engineers and data scientists. - Provide technical coaching, career development, and performance management. - Foster a culture of ownership, experimentation, and rapid iteration. - Help scale the AI team through hiring and organizational development. Project & Cross-Functional Collaboration - Partner with Product, Engineering, Data, and Platform teams to shape the AI roadmap. - Translate product requirements into technical architectures and execution plans. - Drive AI initiatives from research and prototyping through production deployment. AI Quality, Evaluation & Experimentation - Establish rigorous evaluation frameworks for generative AI and ML systems. - Implement both automated evaluation pipelines and human-in-the-loop review processes. - Monitor system performance and continuously improve models through experimentation and feedback loops. Platform & Infrastructure - Collaborate with platform and DevOps teams to build scalable AI infrastructure and services. - Develop reusable tooling for model training, deployment, monitoring, and experimentation. - Ensure AI systems are cost-efficient, observable, and maintainable at scale. What We're Looking For Experience - Bachelor’s or Master’s degree in Computer Science, Engineering, Statistics, or a related field. - 7+ years of experience building production-grade AI/ML systems. - 2+ years leading or managing ML/AI teams. - Experience delivering both traditional ML models and generative AI systems in production. - Experience building multimodal systems involving audio, video, or sensor data. - Demonstrated expertise in model evaluation, including automated testing and human review protocols. - Experience operationalizing models using modern MLOps practices. Technical Skills - Strong hands-on experience with Python and modern ML frameworks (PyTorch, TensorFlow, Hugging Face). - Experience working with LLMs and AI orchestration frameworks. - Deep understanding of the end-to-end ML lifecycle, including data pipelines, training, evaluation, deployment, and monitoring. - Familiarity with cloud-native ML infrastructure and distributed systems. Leadership - Strong mentorship and people leadership skills. - Ability to communicate complex technical concepts clearly to technical and non-technical stakeholders. - Proven ability to lead teams with clarity, empathy, and accountability. Delivery - Track record of delivering production AI systems with measurable user impact. - Experience managing cross-functional AI initiatives from ideation to production. - Ability to balance technical innovation with pragmatic execution. Preferred Qualifications - Experience building AI systems in EdTech or education-focused products. - Experience developing retrieval-augmented generation (RAG), agentic systems, or AI copilots. - Experience working with real-time AI systems (speech, vision, or multimodal pipelines). - Experience deploying multimodal models involving text, audio, image, or video inputs. The annual salary range for this position is $195,000 - $220,000 USD or $160,000 - $190,000 CAD, plus equity. Please note that the final offer amount is determined by multiple factors, including geographic location as well as candidate experience, and may vary from the amounts listed above​. What is it like to work at Paper? You will: - Be joining a remote-first company with a collaborative, mission-driven culture working together to write the next chapter of Paper! - Have opportunities to connect in person throughout the year, even while working remotely day-to-day. - Be part of an exciting new era of growth, with fresh leadership, a bold product vision, and a redefined charter. - Thrive in a fast-moving, build-from-scratch environment where agility and critical thinking guide decisions, collaboration is built on trust and healthy challenge, and every team member takes ownership to deliver real customer impact and grow every day. Additional Benefits: - Comprehensive & competitive compensation, health benefits, retirement plan, stock options, and more. - In addition to vacation days, we provide Paperites with sick days and 4 extra weeks off - including statutory holidays, Paper Days throughout the year, and a full Paper Week from Dec 25 to Jan 1. - A $500 stipend to set-up your workspace and $100 monthly stipends to support with on-going workspace needs. - We support growing families with generous paid parental leave. - Unlimited access to tutoring and educational support for children of Paper employees. You’ll be joining a team of mission-driven builders who care deeply about equity in education, and who thrive in a culture of ownership, velocity, and continuous learning. If you’re energized by challenges, inspired by impact, and ready to help lead a high-growth business through its next phase, we’d love to meet you. We believe diverse teams build better products and we are committed to creating an inclusive environment for all employees. Paper does not discriminate on the basis of race, color, religion, gender, gender orientation, gender expression, sexual orientation, age, national origin, disability, marital status, or military status. Requisition ID R-100301

Job Summary: The AI Developer plays a key role in designing, developing, and deploying intelligent solutions. This role is focused on solving complex business challenges through innovative AI technologies and will collaborate closely with cross-functional teams to ensure timely and high-quality delivery of solutions aligned with defined objectives. DS/Gen/Agentic AI resources with good hands-on skills on: - Current Advancements: Generative AI, Agentic AI, LLM fine-tuning, RAG, GraphRAG, Vector databases, Knowledge Graph, Langchain, Langgraph, etc - Model Deployment: MLOPs pipeline, CI/CD, Model Deployment, Docker, Kubernetes, Azure Cloud, Github, etc - Core Skills: Traditional AI / ML / Data Science skillsets (Predictive, Prescriptive, Descriptive, Statistical, Optimization, Simulation, Natural Language processing, Computer Vision, Image Processing, etc) - Domain: Healthcare, Facets, GuidingCare, etc Note: Domain skills are nice to have and not mandatory. Essential Functions: - Design and implement AI models and algorithms tailored to diverse business challenges - Define and lead the architecture of Generative AI platforms, including large language models (LLMs), vector databases, and inference pipelines - Maintain deep expertise in modern generative AI technologies such as Knowledge Graphs, OpenAI, LLaMA, Python, LangChain, vectorization, embeddings, semantic search, Retrieval-Augmented Generation (RAG), Infrastructure as Code (IaC), and Streamlit - Rapidly prototype proof-of-concept solutions to assess emerging technologies and innovative ideas - Foster innovation and collaboration in a fast-paced environment through a hands-on, imaginative approach and a self-driven, inquisitive mindset - Leverage AI-assisted development tools, including GitHub Copilot and internally developed solutions, to enhance productivity - Apply creative problem-solving techniques to identify and implement process improvements - Assess technical risks and develop effective mitigation strategies to ensure successful project delivery - Collaborate with data scientists, software engineers, and product teams to integrate AI capabilities into production-ready systems - Partner with leadership to evaluate existing services and develop strategies to optimize delivery and support - Perform data preprocessing and analysis on large datasets to uncover actionable insights - Train, validate, and fine-tune machine learning and deep learning models for optimal performance - Deploy models using cloud infrastructure and containerization technologies such as Docker and Kubernetes - Implement and manage MLOps pipelines to automate model training, deployment, monitoring, and lifecycle management - Apply AIOps practices to enhance operational efficiency, automate incident detection, and optimize system performance using AI-driven insights - Continuously monitor model performance and retrain as needed to maintain accuracy and relevance - Stay current with industry trends, tools, and frameworks, and assess their applicability to organizational goals - Document workflows, models, and codebases to support maintainability and knowledge sharing - Provide timely and transparent progress updates to stakeholders, highlighting key milestones, challenges, and proposed solutions - Perform any other job duties as requested Education and Experience: - Bachelor’s degree in Computer Science, Data Science, Artificial Intelligence or related field, or equivalent years of relevant work experience is required - Master’s degree is preferred - Minimum of five (5) years of experience in developing and deploying AI/ML models is required - Experience with cloud platforms (AWS, Azure, GCP) and MLOps tools Is required - Experience with Agile methodologies is required Competencies, Knowledge, and Skills: - Knowledge of model interpretability and ethical AI practices - Proficiency in Python and libraries such as TensorFlow, PyTorch, Scikit-learn, and OpenCV - Strong analytical, evaluative and problem-solving abilities - Strong understanding of data structures, algorithms, and software engineering principles - Excellent problem-solving skills and attention to detail - Strong communication and collaboration abilities - Knowledge of healthcare and managed care Preferred Licensure and Certification: - AI / Data Science certifications or credentials are preferred Working Conditions: - General office environment; may be required to sit or stand for extended periods of time - Occasional travel may be required to meet with stakeholders and development teams Compensation Range: $94,100.00 - $164,800.00CareSource takes into consideration a combination of a candidate’s education, training, and experience as well as the position’s scope and complexity, the discretion and latitude required for the role, and other external and internal data when establishing a salary level. In addition to base compensation, you may qualify for a bonus tied to company and individual performance. We are highly invested in every employee’s total well-being and offer a substantial and comprehensive total rewards package. Compensation Type (hourly/salary): Salary Organization Level Competencies - Fostering a Collaborative Workplace Culture - Cultivate Partnerships - Develop Self and Others - Drive Execution - Influence Others - Pursue Personal Excellence - Understand the Business This job description is not all inclusive. CareSource reserves the right to amend this job description at any time. CareSource is an Equal Opportunity Employer. We are dedicated to fostering an environment of belonging that welcomes and supports individuals of all backgrounds. #LI-GB1

WE ARE HIRING AI Governance Technical Expert (ISO/IEC 42001) ​​​​​Location: 100% Remote – Global Type: Contracted / Project-Based / Potential Permanent Pay: Competitive; Based on experience and authorized technical scope Travel: Minimal (Remote audit model; periodic participation in accreditation body witness audits when assigned) About Us: RSI Security is a leader in cybersecurity compliance and conformity assessment. We operate an independent Certification Body (CB) aligned with ISO/IEC 17021-1 requirements and are currently pursuing accreditation for ISO/IEC 42001 (Artificial Intelligence Management Systems). We maintain strict separation between our certification and advisory entities to protect the integrity and independence of every audit. Our mission is to build a rigorous, globally respected AI governance certification program that ensures AI Management Systems (AIMS) are assessed with impartiality and technical depth. About the Role: As an AI Governance Technical Expert, you will support ISO/IEC 42001 certification audits by providing specialized subject-matter expertise related to AI lifecycle governance, data governance, and model oversight. This is a Certification Body support role and is distinct from consulting, advisory, implementation, or audit leadership functions. Technical Experts supplement audit team competence but do not independently determine conformity, grade nonconformities, sign audit reports as Audit Team Leader, or participate in certification decisions. You will contribute structured technical analysis to audit teams evaluating AI lifecycles, including design, development, validation, deployment, monitoring, and decommissioning within SaaS and enterprise environments. Technical Experts may pursue formal auditor authorization through RSI’s documented competence and authorization framework. Any transition to an auditor role requires full completion of competence evaluation, training, witness audit requirements, and formal authorization prior to performing audit or certification decision activities. What You’ll Do - Provide Technical Lifecycle Expertise: Support audit teams in evaluating AI governance controls across the lifecycle, including model governance, data governance, human oversight, and risk integration. - Review Technical Artifacts: Analyze technical documentation, system descriptions, governance frameworks, validation records, and lifecycle evidence to provide structured input to the Audit Team Leader. - Participate in Audit Interviews: Contribute domain expertise during interviews related to AI model development, validation practices, monitoring controls, and enterprise governance structures. - Support Risk-Based Evaluation: Assist in assessing alignment with ISO/IEC 23894 AI risk management principles and integration into lifecycle governance processes. - Operate Within Impartiality Guardrails: Comply with RSI’s formal independence and conflict-of-interest controls, including cooling-off requirements and periodic attestations. - Engage Under Oversight: Participate in accreditation body witness audits when assigned, demonstrating technical competence under structured external oversight. Competence & Authorization Authorization as a Technical Expert is granted through RSI’s documented competence evaluation and authorization framework. Candidates will undergo structured evaluation of: - AI Technical & Lifecycle Competence: Demonstrated understanding of AI lifecycle stages, model governance concepts, data governance principles, and risk-based AI oversight. - Sector / Contextual Competence: Familiarity with SaaS / Enterprise AI governance environments, including enterprise IT governance structures and organizational oversight models. - Independence Verification: Completion of conflict-of-interest screening and confirmation of no prohibited advisory involvement. - Ongoing Monitoring: Performance review by Audit Team Leaders, quality review of technical input, and periodic independence attestation. Technical Experts are authorized within defined technical categories and sector scopes. Assignment shall not occur outside authorized domains. What You’ll Bring - Experience: 7+ years in AI governance, data governance, model risk management, cybersecurity governance, enterprise risk, or related technical oversight functions. - AI Governance Depth: Strong understanding of AI lifecycle stages, model validation practices, data lifecycle controls, documentation governance, and human oversight mechanisms. - Enterprise Context Awareness: Familiarity with SaaS architectures (high-level), enterprise IT governance structures, and organizational AI oversight frameworks. - Structured Analytical Thinking: Ability to evaluate evidence objectively and provide disciplined, audit-support input rather than advisory recommendations. - Professional Integrity: Commitment to independence, impartiality, and operating within clearly defined role boundaries. Why Join RSI? You will be joining one of the emerging leaders building ISO/IEC 42001 certification capabilities globally. We offer a 100% remote work environment, access to structured audit workflow tools, and a culture that values technical precision and ethical independence above all else. RSI Security is an Equal Opportunity Employer. We prioritize competence, qualifications, and the integrity of the certification process in all hiring decisions.