Lead AI/ML Architect

About the job

We are seeking a Machine Learning Product Architect to define, scale and guide the architectural vision for our AI, ML, and GenAI products. This is a senior, highly visible role that sits at the intersection of product strategy, technical architecture, and applied machine learning — shaping how we design, deliver, and scale intelligent systems across our business. While you won’t directly manage a team, you will serve as a senior partner across engineering, product, and clinical organizations — helping set direction, unlock execution, and scale AI/ML impact across our platforms.

Our business is growing. Our customer needs are evolving. And our platform is advancing rapidly, especially as we embed more AI-native capabilities into our products. Today, our AI, GenAI and machine learning capabilities are fueling a new era in healthcare — powering intelligent systems that help people receive care outside the hospital and supporting providers with insights that enable better outcomes and lower costs. With one of the largest actionable datasets in the industry, we’re uniquely positioned to shape how healthcare is delivered across care settings, from home to post-acute to long-term care.

This role is for someone who thrives in ambiguity, believes architecture is a team sport, and has a proven record of bringing ML and GenAI-driven systems into production at scale.

Location: San Diego (Hybrid)

Let’s talk about the role.

As a Machine Learning Product Architect, you will own the end-to-end architecture of AI/ML/GenAI systems that empower our software products with advanced AI capabilities. You will collaborate with cross-functional teams including business product managers, data scientists, machine learning engineers, and software engineers to design and implement scalable AI. Your work will enable the integration of model training and inference in production environments, ensuring that both the data source and output are optimized for performance and accuracy. You will also work with leadership to communicate and demonstrate the value and impact of machine learning architectures.

Let's talk about responsibilities.

• Architect scalable ML and GenAI solutions across model training, inference, and workflow AI automation, ensuring seamless integration across products.
• Partner with product managers to translate business goals into AI-driven technical solutions that deliver measurable impact.
• Deliver solutions that balance enterprise standards with bespoke innovation, combining platforms and models to meet both organizational and market needs.
• Act as a strategic architect, focusing two-thirds on strategic direction and solution design, and one-third on initiative deep dives, team mentorship, and execution acceleration.
• Lead the creation of Architectural References to demonstrate scalable approaches, reference patterns, and best practices.
• Provide leadership in MLOps and GenAI infrastructure — model versioning, monitoring, CI/CD pipelines, and deployment frameworks.
• Collaborate with data scientists and ML engineers to ensure architectures meet the unique needs of different model types (ML, DL, GenAI, multi-modal).
• Evangelize and promote AI/ML adoption across the organization, serving as a trusted advisor and visible champion of production-ready AI.
• Evaluate emerging AI, GenAI, and cloud-native technologies; make recommendations for adoption at scale.
• Define, Collaborate and implement governance, compliance, and security strategies for responsible AI use, ensuring adherence to regulatory and ethical standards.
• Optimize ML and GenAI workloads for performance, reliability, and cost efficiency.
• Serve as the technology scout, evaluating and integrating emerging AI/ML tools and methodologies to evolve our tech stack strategically

Let's talk about qualifications and experience.

• Bachelor’s or Master’s degree in Computer Science, AI/ML, or related field.
• 8+ years of relevant experience with strong exposure to production-deployed AI/ML systems.
• Proven success in scaling AI/ML and GenAI architectures from concept to production.
• Deep understanding of ML algorithms, GenAI architectures (LLMs, embeddings, RAG, Agentic), and LLM pipeline workflows.
• Strong coding proficiency in Python (additional languages a plus).
• Knowledge of modern software architecture principles and design patterns.
• Strong communication and influencing skills to engage technical and non-technical stakeholders.
• Certifications in cloud architecture or ML/GenAI technologies (preferred).
• Portfolio showcasing production-deployed ML/GenAI systems with business impact.

Let’s talk about what you can expect.

• A supportive environment that focuses on people's development and best implementation
• The opportunity to evangelize AI across healthcare and directly influence its adoption.
• Exposure to inclusive global teams, with open collaboration and idea sharing. We want your ideas!
• Be supported both inside and outside of the work environment.
• The opportunity to build something that matters and see your work improve outcomes at scale.
• Dream big, iterate and experiment to drive innovation.

Joining us is more than saying “yes” to making the world a healthier place. It’s discovering a career that’s challenging, supportive and inspiring. Where a culture driven by excellence helps you not only meet your goals, but also create new ones. We focus on creating a diverse and inclusive culture, encouraging individual expression in the workplace and thrive on the innovative ideas this generates. If this sounds like the workplace for you, apply now! We commit to respond to every applicant.