CVS Health

Staff Machine Learning Engineer, Security

CVS Health

full-time

Posted on:

Origin:  • 🇺🇸 United States • California

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Salary

💰 $130,295 - $260,590 per year

Job Level

Lead

Tech Stack

CloudGrafanaPrometheusPythonPyTorchTensorflowTerraform

About the role

  • At CVS Health, we’re building a world of health around every consumer and surrounding ourselves with dedicated colleagues who are passionate about transforming health care. As the nation’s leading health solutions company, we reach millions of Americans through our local presence, digital channels and more than 300,000 purpose-driven colleagues – caring for people where, when and how they choose in a way that is uniquely more connected, more convenient and more compassionate. Position Summary CVS health is looking for a Senior Data Science Engineer to help with designing systems that utilize data-oriented programming languages and visualization software to explore, analyze, and interpret large volumes of data in various forms and solve complex business problems. This pay range represents the base hourly rate or base annual full-time salary for all positions in the job grade within which this position falls. This position is eligible for a CVS Health bonus, commission or short-term incentive program in addition to the base pay range listed above. This position also includes an award target in the company’s equity award program. Great benefits for great people We take pride in our comprehensive and competitive mix of pay and benefits – investing in the physical, emotional and financial wellness of our colleagues and their families to help them be the healthiest they can be.

Requirements

  • 7+ years of coding experience using Python with expertise in solution and software development. 7+ years in DevOps/MLOps and a deep understanding of software engineering principles. 7+ years of experience in TensorFlow and PyTorch, with additional cloud platform familiarity. Proven ability to manage the production lifecycle of an MLOps pipeline. Deep understanding of model deployment and serving. Experience with orchestration and containerization methodologies. Familiarity with model serving tools such as MLflow, Databricks Serving, SageMaker, etc. (TensorFlow Serving is a plus). Experience implementing CI/CD pipelines for ML projects. Competence in developing automation pipelines (e.g., using GitHub Actions). Proficiency in Infrastructure as Code tools (e.g., Terraform, Databricks Asset Bundles,etc). Strong understanding of monitoring and observability, including logging tools (e.g., Prometheus, Grafana) and drift detection.