Platform Engineer Machine Learning (Utah)

Responsibilities

• Develop and enhance the machine learning platform to manage the full model life cycle
• Build frameworks and tools to enable the data science team develop ing and enhanc ing predictive model s , support scalable real-time predictions in production
• Design and implement data engineering solutions for model training
• Expand NLP capabilities with advanced analysis techniques to improve text understanding
• Design and implement high-performance, scalable services and applications
• Collaborate with team members to create integrated solutions and ensure timely delivery of quality software and documentation
• Understand and a dhere to development standards for consistency across teams
• Perform in-depth technical and performance analyses to troubleshoot production issues
• Monitor and maintain production systems for reliability and efficiency

Requirements

• Minimum Requirements (Education, certifications and experience):
• Bachelor's degree in Computer Science or related area , Masters preferred
• 7 + years of professional experience writing Python or Java code , with at least 3 years building data platforms
• Expert proficiency with SQL
• NLP
• Seasoned practitioner of engineering best practices such as CI/CD and automated testing
• Comfort working in a Linux environment
• Passion for exploring, applying and following the evolution of cutting edge technologies related to AI, machine learning, NLP and large scale data processing
• Professional experience with MLOps , Docker, Kubernetes, relational databases (PostgreSQL preferred), Kafka, REST API design, and microservices application architectures
• Experience with public cloud solutions, such as AWS or GCP
• Proven track record of successful delivery of progressively complex technical projects
• Coaching and mentoring junior engineers in the team
• Team player DNA with a positive, self-starter attitude
• Attention to detail, highly organized, with an absolute focus on quality of work
• Preferred Requirements:
• Familiarity with ClearML , Triton, PyTorch , and TensorFlow
• Familiarity with statistics and healthcare domain
• Proven expertise in successful large project/build management and execution
• ABOUT WAYSTAR
• Through a smart platform and better experience, Waystar helps providers simplify healthcare payments and yield powerful results throughout the complete revenue cycle.
• WAYSTAR PERKS
• Competitive total rewards (base salary + bonus, if applicable)
• Customizable benefits package (3 medical plans with Health Saving Account company match)
• We offer generous paid time off for our non-exempt team members, starting with 3 weeks + 13 paid holidays, including 2 personal floating holidays. We also offer flexible time off for our exempt team members + 13 paid holidays
• Paid parental leave (including maternity + paternity leave)
• Education assistance opportunities and free LinkedIn Learning access
• Free mental health and family planning programs, including adoption assistance and fertility support
• 401(K) program with company match
• Pet insurance
• Employee resource groups
• Waystar is proud to be an equal opportunity workplace. We celebrate, value, and support diversity and inclusion. Qualified applicants will receive consideration for employment without regard to race, color, religion, age, sex, national origin, disability status, genetics, marit

Benefits

Additional Information

ABOUT THIS POSITION We are looking for a Machine Learning Platform Engineer - Backend Services that will help us build out the platform that supports the training and application of our predictive models and performs deep analysis to extract machine consumable meaning from unstructured clinical documentation. You will be joining a small team that has become one of the top players in our field in just two years. Because we work on the cutting edge of a lot of technologies, we need someone who is a creative problem solver, resourceful in getting things done, and productive working independently or collaboratively. You will be accessing our enormous amount of data to help drive our future innovation.

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