Job Description
Title: Machine Learning Engineer II
Location: United States, Remote
ABOUT ARTERA
Our Mission: Make healthcare #1 in customer service.
What We Deliver: Artera (formerly WELL Health) is the patient communication platform that delivers happier staff, healthier patients, and more profitable organizations. We enable two-way conversations between patients and their healthcare teams through secure, multilingual messaging across multiple channels including text, email, and telephone. By unifying disjointed touchpoints into a single, intuitive channel, Artera fuels connected patient experiences and empowers organizations to deliver the best customer service imaginable.
Our Impact: Artera helps 500+ healthcare providers facilitate more than 1 billion messages for 40+ million patients annually.
Our award-winning culture: In 2021, Artera was named #10 on the Forbes list of America’s Best Startup Employers, as well as being named one of Deloitte’s Fast 500 (#133). Artera was also recognized as one of the Best Midsize Companies to Work for in Los Angeles by Built In in 2022, and has been ranked on the Inc. 5000 list of fastest-growing private companies for three consecutive years.
SUMMARY
AI is central to Artera’s ability to improve patient experiences, optimize workflows and empower health systems to deliver the best quality care possible. With the latest developments in AI, new and exciting opportunities emerged, further solidifying AI as a key strategic focus of Artera’s product vision.
To make it happen, Artera’s Data team is adding additional headcount to our Machine Learning function and we are looking for a talented Machine Learning Engineer. In this role, you will be primarily working with Product Managers, Software Engineers and Data Scientists to design and deliver customer-facing ML solutions. During this process, you will be developing ML workflows and end-to-end pipelines for data preparation, training, deployment, monitoring (ensure architectural quality) and model performance.
If you are a self-starter who enjoys applying ML expertise to make a difference in health care, this is the opportunity for you.
RESPONSIBILITIES
- Scope, design, build and ship end-to-end machine learning models
- Drive exploratory data analysis to test, define and iterate from idea to proof-of-concept
- Build feature pipeline with Analytics Engineers to automate feature extraction and monitoring
- Build and maintain Sagemaker pipelines to automate inference generation and work with product engineering for integration into product
- Own Sagemaker automated testing and deployment processes for machine learning models
- Develop and own AWS Sagemaker managed framework for performance monitoring, evaluation and automated retraining
REQUIREMENTS
- MS or above in quantitative field
- 3+ years of full-time experience in building machine learning products
- End-to-end experience designing and shipping machine learning features
- Strong proficiency in Python, and experiences with machine learning framework e.g. TensorFlow, PyTorch or Keras
- Hands-on experience with MLOps in cloud infrastructure, ideally AWS
- Proven records in choosing the right solution for the right problem
- Great communication skills and business mindset
BONUS
- Proficiency at NLP
- Experience with HL7 FHIR format, EHR data
- Knowledge with US health system
- Experience with dbt, Snowflake
