Location: Staff AI Researcher Workplace: remote Category: Engineering Job Description: Job Duties/Description: The Staff AI Researcher is responsible for developing advanced artificial intelligence solutions that improve health outcomes for millions of patients by empowering primary care physicians with technology that keeps patients healthy and prevents unnecessary hospitalizations. The Staff AI Researcher collaborates with engineering and analytics teams to bring AI technologies into existing products and workflows. Additionally, the role involves training, fine-tuning, and using AI models harnessing knowledge from extensive data sets of medical records, diagnoses, claims, and prescriptions collected from millions of patients across the country. Primary duties include building working prototypes using off-the-shelf and novel AI techniques to deliver higher levels of optimization for the company; working with large, complex data sets and solving difficult, non-routine analytical problems to harvest data; redesigning existing pipelines and systems to meet growing data and query needs; implementing techniques for fine-tuning and adapting pre-trained generative models to specific healthcare domains or tasks; developing evaluation metrics and benchmarks to assess the quality and performance of AI/ML models; designing and implementing feature engineering pipelines, including data processing, feature extraction, and transformation to optimize model performance; setting and upholding standards for engineering processes, including style and code checking, test harnesses, and release packaging; and delivering working proof-of-concept solutions that balance speed, scalability, and time-to-market considerations. This is a remote work position. Multiple positions are available. Minimum Requirements Must have a Master’s degree or foreign degree equivalent in Computer Science or a related quantitative field and six (6) years of machine learning and statistical analysis experience. The position also requires demonstrated knowledge and experience with the following: three (3) years of deep learning and large language model experience; three (3) years of Python experience; three (3) years of proficiency in selecting the right tools given a data optimization problem; addressing challenges from incomplete, unrepresentative, and mislabeled data; and large-scale distributed systems at scale and statistical software (e.g., Spark). This is a remote work position. Who We Are: Aledade, a public benefit corporation, exists to empower the most transformational part of our health care landscape - independent primary care. We were founded in 2014, and since then, we've become the largest network of independent primary care in the country - helping practices, health centers and clinics deliver better care to their patients and thrive in value-based care. Additionally, by creating value-based contracts across a wide variety of health plans, we aim to flip the script on the traditional fee-for-service model. Our work strengthens continuity of care, aligns incentives and ensures primary care physicians are paid for what they do best - keeping patients healthy. If you want to help create a health care system that is good for patients, good for practices and good for society - and if you're eager to join a collaborative, inclusive and remote-first culture - you've come to the right place. What Does This Mean for You? At Aledade, you will be part of a creative culture that is driven by a passion for tackling complex issues with respect, open-mindedness and a desire to learn. You will collaborate with team members who bring a wide range of experiences, interests, backgrounds, beliefs and achievements to their work - and who are all united by a shared passion for public health and a commitment to the Aledade mission. In addition to time off to support work-life balance and enjoyment, we offer the following comprehensive benefits package designed for the overall well-being of our team members: - Flexible work schedules and the ability to work remotely are available for many roles - Health, dental and vision insurance paid up to 80% for employees, dependents and domestic partners - Robust time-off plan (21 days of PTO in your first year) - Two paid volunteer days and 11 paid holidays - 12 weeks paid parental leave for all new parents - Six weeks paid sabbatical after six years of service - Educational Assistant Program and Clinical Employee Reimbursement Program - 401(k) with up to 4% match - Stock options - And much more! At Aledade, we don’t just accept differences, we celebrate them! We strive to attract, develop and retain highly qualified individuals representing the diverse communities where we live and work. Aledade is committed to creating a diverse environment and is proud to be an equal opportunity employer. Employment policies and decisions at Aledade are based on merit, qualifications, performance and business needs. All qualified candidates will receive consideration for employment without regard to age, race, color, national origin, gender (including pregnancy, childbirth or medical conditions related to pregnancy or childbirth), gender identity or expression, religion, physical or mental disability, medical condition, legally protected genetic information, marital status, veteran status, or sexual orientation. Privacy Policy: By applying for this job, you agree to Aledade's Applicant Privacy Policy available at https://www.aledade.com/privacy-policy-applicants

• Design advanced computer science problems focused on reasoning and conceptual understanding • Create structured reference solutions with clear logic and technical explanations • Evaluate AI-generated answers for correctness, reasoning quality, completeness, and clarity • Identify edge cases, logical flaws, and weak reasoning patterns in model outputs • Review complex topics across algorithms, systems, databases, networking, security, and theory • Contribute to benchmark and evaluation quality improvements • Provide detailed feedback to support AI model training and evaluation • Collaborate with researchers and reviewers on problem refinement • Maintain high-quality standards and consistent evaluation methodology

• Post-training for model development • Develop novel algorithms that improve model reliability, controllability, and alignment • Design and run experiments that shape model behavior • Partner with infrastructure teams to build scalable, reproducible workflows • Contribute to publications, patents, and external research visibility • Drive human-in-the-loop evaluation with high annotation quality • Communicate technical risks, limitations, and trade-offs clearly to leadership

• Drive foundational and applied research in reasoning engines, planning architectures, and decision-making frameworks at scale. • Advance techniques in LLM/LRM post-training, reinforcement learning–based decisioning, and knowledge-integrated agents. • Design methods for plan induction, value estimation, and contingency modeling within intelligent agents. • Explore and validate protocols for distributed reasoning and joint planning among cooperative agents in multi-agent systems. • Architect RPD systems that integrate post-trained LLMs/LRMs, graph-structured memory (e.g., KGs), and RL-driven controllers. • Design recursive task planners, search-based or policy-based reasoners, and belief-state trackers that can interoperate with large model substrates. • Ensure modularity and extensibility through multi-agent frameworks, agentic substrates, and declarative planning pipelines. • Define communication protocols, coordination strategies, and cross-agent knowledge alignment mechanisms to foster emergent cooperative intelligence.