Hi, we're Gravie. Our mission is to improve the way people purchase and access healthcare through innovative, consumer-centric health benefit solutions that people can actually use. Our industry-changing products and services are developed and delivered by a diverse group of unique people. We encourage you to be your authentic self - we like you that way.
We are looking for a Machine Learning Engineer who is passionate about harnessing the power of AI/ML to make a real difference in the healthcare sector. If you are skilled in both machine learning engineering and data engineering, and eager to apply your expertise in a vibrant, tech-driven environment, Gravie is your destination.
You will:
•Develop ML infrastructure with web services/APIs, batch jobs, and scheduling, focusing on the model life cycle, monitoring, testing, and data quality.
•Automate feature engineering and data processing, developing data pipelines to ensure smooth and efficient workflows for model training and deployment, and familiarity with Spark.
•Use AWS tools like Sagemaker, Redshift, Glue, EMR, and Lambda to create advanced cloud-based ML infrastructures.
•Collaborate with ML scientists to streamline large-scale experiments through the development of tools and scripts, with the option to engage in model development and research cycles based on your personal interests.
•Collaborate across teams to ensure that ML projects are in sync with business objectives and strategic goals, translating complex data insights for diverse stakeholders.
•Demonstrate commitment to our core competencies of being authentic, curious, creative, empathetic and outcome oriented.
You bring:
•4 years of hands-on experience building ML products end-to-end and productionizing ML models.
•Strong background in data engineering concepts, including data pipelines, warehousing, and cloud architectures.
•Solid experience with software engineering best practices, command line, version control (Git), and infrastructure as code (AWS CDK or Terraform), and proficiency in Python.
•Experience with AWS cloud environments and familiarity with DevOps, CI/CD, containerized development and orchestration.
•Experience with standard machine learning tools, libraries, and infrastructure solutions such as Scikit-learn, Pandas, PyTorch, TensorFlow is a plus.
•Experience in dynamic startup environments, adept at rapid adaptation and contributing significantly to the company's vision and culture.
•Exceptional ability to establish a ML infra roadmap, articulate complex technical ideas, and collaborate effectively with various business and technical stakeholders.
Extra credit:
•Experience in the healthcare or insurance sectors, especially with HIPAA compliance.
•Familiarity with data visualization tools (e.g., Tableau, Power BI) and additional AWS services.
•Bachelor's or Master's degree in computer science, engineering, or a related field
Competitive pay is standard. Our unique benefits program is the gravy, i.e., the special sauce that sets our compensation package apart. In addition to standard benefits, Gravie's package includes alternative medicine coverage, flexible PTO, 10 weeks paid parental leave, paid holidays, cell phone reimbursement, education reimbursement, and 1 week of paid paw-ternity leave just to name a few.
Join us at Gravie, where your machine-learning engineering skills will play a crucial role in shaping the future of healthcare benefits. We are excited to see how your expertise will contribute to our mission.