• Design, implement and validate high-reliability, distributed platforms for machine learning, natural language processing, and LLMs. • Create, debug, interpret and improve production machine learning and natural language processing models. • Build the tools and validation processes that help Clover translate insights into action at scale. • Use existing commercial and open-source tools to create a robust production platform. • Work closely with Clover's Data Science and Engineering teams to ensure that the ML/NLP/LLM Platform is providing real value. • Document, iterate, and provide tutorials to ensure Data Scientists are able to use your tools easily.

At Counterpart Health, we are transforming healthcare and improving patient care with our innovative primary care tool, Counterpart Assistant. By supporting Primary Care Physicians (PCPs), we are able to deliver improved outcomes to our patients at a lower cost through early diagnosis and longitudinal care management of chronic conditions. Clover's Data Science team is charged with leveraging our data—our most important asset—to generate value for our members. From understanding how the member experience impacts clinical outcomes to making our home visits more efficient and effective, our team pushes out insights central to executing on our core mission. And our impact is tremendous: you'll be able to point to one of our members and say, “I helped make that person's life better.” We’re looking for a Senior Machine Learning Engineer to help us build a revolutionary new health care business. Clover uses Machine Learning/Natural Language Processing to leverage our data to help keep beneficiaries healthy and out of the hospital by getting them targeted care. By predicting avoidable adverse events, our ML/NLP/LLM infrastructure is central to working on our central mission, and has a direct impact on our beneficiaries. You will help build systems and tools that support the data needs of a diverse organization and contribute to the expansion of the Machine Learning/Natural Language Processing/LLM capabilities of our Data Platform. As a Senior Machine Learning Engineer, you will: - Design, implement and validate high-reliability, distributed platforms for machine learning, natural language processing, and LLMs. - Create, debug, interpret and improve production machine learning and natural language processing models. - Build the tools and validation processes that help Clover translate insights into action at scale. - Use existing commercial and open source tools to create a robust production platform. - Work closely with Clover's Data Science and Engineering teams to ensure that the ML/NLP/LLM Platform is providing real value. - Document, iterate, and provide tutorials to ensure Data Scientists are able to use your tools easily. You will love this job if: - You want to create impact with your work by finding machine learning-driven insights in the data to unlock value and improve health outcomes for real people. - You are comfortable acting autonomously in ambiguous and changing environments. - You value collaboration and feedback. You can communicate technical vision in clear terms— to your teammates and across the technology team more broadly. You are willing and able to help your teammates grow by demonstrating best practices, providing (and receiving) respectful and constructive feedback, and disclosing your unique insights with everyone. - You enjoy working in a fluid environment, defining priorities that adapt to our larger goals. You can bring clarity to ambiguity while remaining open-minded to new information that might change your mind. - You are not hesitant to jump in to help fix things that are broken and you are encouraged to make sustainable systems. You are happy to fill in the gaps to reach a goal where necessary, even if it does not always fit your job description. - You have a genuine interest in what good technology can do to help people and have a positive attitude about tackling hard problems in an important industry. You should get in touch if: - You have 5+ years of experience in Machine Learning Engineering roles in technology enabled companies. Healthcare experience preferred but not required. - You have experience with Python, Python data science libraries (numpy, pandas, sklearn, tensorflow, pytorch, etc.), and deploying Python apps into production environments. - You have experience with Natural Language Processing and/or LLMs. - You have a solid foundation in feature engineering, feature selection, and machine learning techniques. - You have experience interpreting, modifying, and debugging the inputs and outputs of production ML/NLP/LLM models. - You have both built and refactored complex distributed systems, especially ML/NLP/LLM systems. - You have scaled the impact of other engineers and data scientists through mentorship, development of reusable libraries, and documentation. Benefits Overview: - Financial Well-Being: Our commitment to attracting and retaining top talent begins with a competitive base salary and equity opportunities. Additionally, we offer a performance-based bonus program, 401k matching, and regular compensation reviews to recognize and reward exceptional contributions. - Physical Well-Being: We prioritize the health and well-being of our employees and their families by providing comprehensive medical, dental, and vision coverage. Your health matters to us, and we invest in ensuring you have access to quality healthcare. - Mental Well-Being: We understand the importance of mental health in fostering productivity and maintaining work-life balance. To support this, we offer initiatives such as No-Meeting Fridays, monthly company holidays, access to mental health resources, and a generous flexible time-off policy. Additionally, we embrace a remote-first culture that supports collaboration and flexibility, allowing our team members to thrive from any location. - Professional Development: Developing internal talent is a priority for Clover. We offer learning programs, mentorship, professional development funding, and regular performance feedback and reviews. Additional Perks: - Employee Stock Purchase Plan (ESPP) offering discounted equity opportunities - Reimbursement for office setup expenses - Monthly cell phone & internet stipend - Remote-first culture, enabling collaboration with global teams - Paid parental leave for all new parents - And much more! About Counterpart Health: In 2018, Clover Health set out to do something unprecedented: build a clinically intuitive, AI-enabled solution that fits within physicians' workflows to help support the earlier diagnosis and management of chronic conditions. Years later, that vision is a reality, with thousands of practitioners using Counterpart Assistant during patient visits to improve disease management, reduce medical expenses, and drive success in value-based care. With an exceptional team of value-based care and technology experts, Counterpart Health is driving value-based care at the speed of software. Counterpart Health is a subsidiary of Clover Health. From Clover’s inception, Diversity & Inclusion have always been key to our success. We are an Equal Opportunity Employer and our employees are people with different strengths, experiences, perspectives, opinions, and backgrounds, who share a passion for improving people's lives. Diversity not only includes race and gender identity, but also age, disability status, veteran status, sexual orientation, religion and many other parts of one’s identity. All of our employee’s points of view are key to our success, and inclusion is everyone's responsibility. #LI-REMOTE Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. We are an E-Verify company. Final pay is based on several factors including but not limited to internal equity, market data, and the applicant’s education, work experience, certifications, etc. A reasonable estimate of the base salary range for this role is: $150,000—$200,000 USD

• Develop new models end-to-end, from understanding product requirements to implementation and deployment. • Align with various stakeholders, including Product Managers, Data Engineers, and Backend Engineers to ensure seamless integration of ML solutions into the product ecosystem. • Develop models: design, train, evaluate, and iterate on ML models using modern techniques tailored to real business problems. • Put models into production with robust technical implementation and quality assurance processes. • Create an ML Ops framework for the team to ensure our models scale effectively with proper monitoring and alerts (e.g., model drift detection, performance tracking, automated retraining pipelines). • Share best practices within the ML team, contributing to internal knowledge, tooling improvements, and mentoring peers.

• Architect and deliver cutting-edge ML solutions using MLOps and best practices, fostering creativity in project execution • Design systems to enable rapid ML development, high availability, and clear observability • Develop tools, systems, and automation to support ML solutions, ensuring efficiency, scalability, and rapid development • Collaborate closely with product teams to develop APIs, maintain ML infrastructure, and integrate machine learning features into products • Provide technical leadership, mentor less experienced ML engineers and scientists, and define team best practices and processes • Lead in the ML space by introducing new technologies and techniques, and applying them to Workiva's strategic initiatives • Communicate complex technical issues to both technical and non-technical audiences effectively • Deliver, update, and maintain machine learning infrastructure to meet evolving needs • Host ML models to product teams, monitor performance, and provide necessary support • Write automated tests (unit, integration, functional, etc.) with ML solutions in mind to ensure robustness and reliability • Debug and troubleshoot components across multiple service and application contexts, engaging with support teams to triage and resolve production issues • Participate in on-call rotations, providing 24x7 support for all of Workiva’s SaaS hosted environments • Perform Code Reviews within your group’s products, components, and solutions, involving external stakeholders (e.g., Security, Architecture)