Machine Learning Platform Engineer - Backend Services

ABOUT THIS POSITION

Machine Learning Platform Engineer - Backend Services
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.

WHAT YOU'LL DO

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 developing and enhancinge predictive model 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 adhere 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

WHAT YOU'LL NEED

What You’ll Need
Minimum Requirements (Education, certifications and experience):

• Bachelor’s degree in Computer Science or related area

• 3+ years of professional experience writing Python or Java code

• Intermediate proficiency with SQL

• Experience with 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 Docker, Kubernetes, relational databases (PostgreSQL preferred), REST API design, and microservices application architectures

• Experience with public cloud solutions, such as AWS or GCP

• Team player DNA with a positive, self-starter attitude

• Attention to detail, highly organized, with an absolute focus on quality of work

Preferred Requirements:

• Professional experience with MLOps, Kafka

• Familiarity with ClearML, Triton, PyTorch, and TensorFlow

• Familiarity with statistics and healthcare domain

• Proven expertise in successful large project/build management and execution

• Demonstrated ability to manage multiple work streams simultaneously and efficiently

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, marital status, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws.

This applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.