Machine Learning Architect

Datavant is a data logistics company for healthcare whose products and solutions enable organizations to move and connect data securely. We are a data logistics company for healthcare whose products and solutions enable organizations to move and connect data securely. Datavant has a network of networks consisting of thousands of organizations, more than 70,000 hospitals and clinics, 70% of the 100 largest health systems, and an ecosystem of 500+ real-world data partners.

By joining Datavant today, you’re stepping onto a highly collaborative, remote-first team that is passionate about creating transformative change in healthcare. We hire for three traits: we want people who are smart, nice, and get things done. We invest in our people and believe in hiring for high-potential and humble individuals who can rapidly grow their responsibilities as the company scales. Datavant is a distributed, remote-first team, and we empower Datavanters to shape their working environment in a way that suits their needs.

Are you a seasoned Machine Learning Architect looking to make a real impact in healthcare data logistics? Join Datavant as our ML Architect and lead the design of ML Ops and Model Ops platforms. Your expertise will drive the acceleration and scalability of AI product delivery, revolutionizing healthcare data logistics. If you're ready to shape the future of healthcare with innovative ML solutions, join us at Datavant and make a difference.

You will:

• Design and architect ML Ops and Model Ops platforms for healthcare data logistics.
• Select and integrate tools for ML workflow optimization and efficiency.
• Deploy and monitor machine learning models in production environments.
• Optimize scalability and performance of ML infrastructure.
• Ensure security and compliance of ML operations with healthcare data regulations.
• Collaborate cross-functionally with teams to align ML initiatives with business objectives.
• Document and share knowledge to promote continuous learning and improvement.
• Lead and manage ML Ops and Model Ops projects, providing mentorship and guidance.

What you will bring to the table: 

• Deep expertise in machine learning concepts and model deployment.
• Proficiency in designing scalable ML Ops and Model Ops platforms.
• Strong technical skills in relevant programming languages and frameworks.
• Knowledge of healthcare data logistics and regulatory requirements.
• Exceptional problem-solving and analytical abilities.
• Effective communication and collaboration skills.
• Leadership and project management capabilities.
• Innovative mindset and commitment to continuous improvement.
• Adaptability to evolving business needs and technology landscapes.
• Attention to detail to ensure accuracy and reliability in ML operations.

Bonus points if:

• Experience working healthcare industry, delivery of AI product for healthcare and building ML ops platform to accelerate Model and ML Ops lifecycle.

We are committed to building a diverse team of Datavanters who are all responsible for stewarding a high-performance culture in which all Datavanters belong and thrive. We are proud to be an Equal Employment Opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, sex, sexual orientation, gender identity, religion, national origin, disability, veteran status, or other legally protected status.

Our compensation philosophy is to be externally competitive, internally fair, and not win or lose on compensation. Salary ranges for this position are developed with the support of benchmarks and industry best practices. 

We’re building a high-growth, high-autonomy culture. We rely less on job titles and more on cultivating an environment where anyone can contribute, the best ideas win, and personal growth is driven by expanding impact. The range posted is for a given job title, which can include multiple levels. Individual rates for the same job title may differ based on their level, responsibilities, skills, and experience for a specific job. The estimated salary range for this role is  [$X,XXX - $X,XXX].

At the end of this application, you will find a set of voluntary demographic questions. If you choose to respond, your responses will be anonymous and used to help us identify areas of improvement in our recruitment process. (We can only see aggregate responses, not individual responses. In fact, we aren’t even able to see if you’ve responded or not.) Responding is your choice and it will not be used in any way in our hiring process.