Role Description We are seeking a master’s-level graduate student to assist with preparing a manuscript for submission to an academic journal. The article has yet to be written but the content exists and can be pulled together quickly, once the journal submission guidelines are understood. The role involves helping navigate the submission process and ensuring the manuscript and supporting materials are formatted and submitted correctly. Responsibilities - Review journal submission guidelines and requirements - Format manuscript according to journal style requirements - Ensure references, tables, and figures meet formatting standards - Prepare submission materials such as cover letter and author information - Assist with uploading and submitting the manuscript through the journal portal - Provide guidance on the overall submission process Qualifications - Current enrollment in a master’s program - Experience with academic writing or journal submissions - Strong attention to detail - Familiarity with citation styles such as APA or AMA - Experience with reference management tools (Zotero, EndNote, Mendeley) is an asset - Journal publishing experience is an asset Requirements - Approximately 15 hours total, with flexibility up to 20 hours+ if required - Work can be completed flexibly over 2–3 weeks Compensation - $30 per hour Location - Remote work is acceptable Suggested Line to Attract Strong Candidates Students in public health, rehabilitation sciences, public policy, health administration, or social sciences are especially encouraged to apply.

Role Description Join Guild at a pivotal moment as we build the AI/ML foundation that will transform how working adults navigate their education and career journeys. As a Senior Applied Scientist, you'll move beyond theoretical models to deliver production AI systems that directly improve member experiences—from augmenting our program and career data to developing agentic solutions and contributing to our Apollo platform's reinforcement learning capabilities. This is a high-impact role where your work ships to production and drives measurable outcomes for the millions of members we serve. - Deliver production AI/ML models that augment Guild's program and career data, empowering downstream product and analytics capabilities. - Launch production agentic data solutions through Databricks that improve information retrieval and synthesis while reducing operational costs. - Contribute to Guild's Apollo platform by developing AI/ML components including our reinforcement learning process and AI memory layer. Here's what you will do in this role to achieve these outcomes: - Design, develop, and deploy production-ready AI/ML models that integrate into the product experience and drive measurable improvements in member outcomes and business performance. - Build robust evaluation frameworks including offline metrics, A/B testing, and monitoring strategies to assess model performance and business impact. - Own the end-to-end model lifecycle: deployment, monitoring, drift detection, retraining, and incident response using Guild's MLOps best practices. - Manipulate and analyze large, complex datasets using Python, SQL, Databricks, MLFlow, dbt, and Snowflake. - Partner with business stakeholders to translate strategic challenges into concrete, lasting AI/ML solutions. - Collaborate with engineering, innovation architects, and technical experts to operationalize models and stay current on emerging AI capabilities. - Influence the technical roadmap and architecture of Guild's AI platform by making principled tradeoffs across model complexity, scalability, latency, and cost. - Translate cutting-edge research (reinforcement learning, foundation models) into pragmatic, scalable solutions while exercising judgment about when ML is the right tool. Qualifications - Shipped AI/ML models to production that drove measurable business or product outcomes (not just research or POCs). - Built and maintained evaluation frameworks that included both offline experimentation and live A/B testing. - Developed data pipelines or ML infrastructure that scaled to support large datasets and multiple downstream consumers. - Translated ambiguous business problems into well-scoped ML solutions—and knew when not to use ML. - Worked cross-functionally with engineering, product, and business teams to operationalize technical solutions. Requirements - Strong proficiency in Python and SQL for data manipulation and model development. - Hands-on experience with modern ML/data platforms (Databricks, MLFlow, Snowflake, dbt or similar). - Deep understanding of the full ML lifecycle: from experimentation through deployment, monitoring, and iteration. - Familiarity with reinforcement learning, foundation models, or agentic AI architectures. - Ability to design rigorous experiments and interpret results to inform product decisions. - Strong communication skills to partner effectively with non-technical stakeholders. - Sound judgment in balancing technical complexity with practical business constraints. Benefits - Access to low-cost, high-quality health care options through Collective Health and Kaiser (due to coverage limitations, Kaiser is currently only available in CA & CO). - Access to a 401k to help save for the future. - Vacation policy to rest and recharge. - 8 days of fully-paid sick leave, to take the time to heal and or recover. - Family-friendly benefits, including 12 weeks of parental leave for non-birthing parents and 18-20 weeks for birthing parents; 2-week ramp-up period for when employees return from a leave of 6 weeks or more; as well as employer-paid short-term and long-term disability, employer-sponsored life insurance, fertility and caregiving benefits. - Well-rounded wellness benefits including free and low cost mental health resources and financial wellbeing support services. - Education benefits and tuition assistance to help your future development and growth.

• Guide intervention strategy and development. • Evaluate the impact of Aledade’s population health interventions. • Use innovative methods to answer pressing business questions. • Design and conduct analyses that leverage rich data sources including national Medicare claims, other payer claims, electronic health records, event notification, and patient-reported data. • Work across teams to understand key performance and policy questions facing the business and bring data to inform strategic and tactical decision making.

• Own post-training strategy for model development — from RLHF and preference optimization to agentic systems and long-horizon reasoning • Develop novel algorithms that improve model reliability, controllability, and alignment • Make principled architectural decisions about when to address challenges at the pre-training, post-training, or system level • Design and run experiments that shape model behavior, robustness, and reasoning quality • Partner with infrastructure teams to build scalable, reproducible post-training workflows • Contribute to publications, patents, and Autodesk's external research visibility • Design evaluation frameworks for long-horizon reasoning, tool use, agentic behavior, safety, and real-world workflow completion • Lead rigorous model analysis and interpretability efforts • Drive human-in-the-loop evaluation with high annotation quality and sound scientific methodology • Establish model readiness criteria and provide go/no-go recommendations for releases • Manage, mentor, and grow a team of AI scientists • Set technical direction and research priorities across post-training and alignment initiatives • Foster a research culture grounded in scientific rigor, reproducibility, and fast iteration • Help recruit world-class talent across ML, RL, alignment, and foundation models • Partner closely with pre-training teams, infrastructure, product organizations, and other stakeholders • Translate research trade-offs into clear, decision-ready guidance for leadership