Bring your heart to CVS Health. Every one of us at CVS Health shares a single, clear purpose: Bringing our heart to every moment of your health. This purpose guides our commitment to deliver enhanced human-centric health care for a rapidly changing world. Anchored in our brand - with heart at its center - our purpose sends a personal message that how we deliver our services is just as important as what we deliver.
Our Heart At Work Behaviors™ support this purpose. We want everyone who works at CVS Health to feel empowered by the role they play in transforming our culture and accelerating our ability to innovate and deliver solutions to make health care more personal, convenient and affordable.We are seeking a highly skilled and passionate Machine Learning Engineer with a strong foundation in data engineering to join our innovative team. In this role, you will bridge the gap between data and impactful machine learning models. You will be responsible for the entire ML lifecycle, from data collection and preprocessing to model development, deployment, and monitoring, leveraging your expertise in data engineering to build robust and scalable solutions.Responsibilities:
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- Design, develop, and deploy scalable and high-performance data pipelines using GCP services (e.g., Dataflow, Dataproc, Pub/Sub, BigQuery, Cloud Storage)
- Develop and implement machine learning models using appropriate algorithms and techniques. This includes model selection, training, tuning, and evaluation.
- Use software development best practices like code review, continuous integration, and continuous delivery (CI/CD), release management, and version control.
- Develop and maintain data quality checks and monitoring systems to ensure data accuracy and completeness.
- Collaborate with data scientists and machine learning engineers to optimize data for model training and inference.
- Build and maintain data infrastructure for AI/ML workloads, including feature stores, model registries, and experiment tracking systems.
- Automate data pipelines and infrastructure using tools like Apache Airflow or similar orchestration platforms.
- Troubleshoot and resolve data-related issues and performance bottlenecks.
- Stay up to date with the latest advancements in data engineering, cloud computing, and AI/ML technologies.
- Work to enhance existing test automation processes, improving efficiency, and reducing manual intervention across environments.
- Partner with teams and serve as cross-functional expert to provide bench-marked solutions to multiple, complex technical projects/initiatives using multiple interlocking technologies.
- Implement data quality checks and monitoring to ensure data accuracy and reliability for model training and prediction.
- 2+ years of experience as a Machine Learning Engineer, with a demonstrable understanding of data engineering principles.
- Strong programming skills in Python and experience with relevant ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).
- Solid understanding of various machine learning algorithms and techniques (e.g., regression, classification, clustering, deep learning).
- Experience with data engineering tools and technologies (e.g., Spark, SQL databases, NoSQL databases, cloud platforms like AWS, GCP, or Azure).
- Experience with MLOps tools and frameworks (e.g., MLflow, Kubeflow, SageMaker).
- Experience with containerization technologies (e.g., Docker, Kubernetes).
- Excellent problem-solving, communication, and collaboration skills.
- Experience with Azure Kubernetes Service (AKS) or Google Kubernetes Engine (GKS) for deploying containerized applications.
- Proficiency with cloud data platforms such as Snowflake and/or BigQuery.
- Experience with big data frameworks like Apache Spark, Google Dataproc, or Databricks.
- Experience with Kafka for real-time data streaming.
- Experience with REST API/Microservice development using Python.
- Experience with orchestrating data workflow using automation tools such as Airflow.
- Retail and/or Healthcare experience and domain knowledge.
- Exposure to DevOps tools such as Jenkins, GitHub, or GitLab for CI/CD pipeline management.
- Experience working in multi-developer environment, using version control
- Required: bachelor's degree in computer science, Engineering, Machine Learning, or related field or equivalent experience.
- Preferred: master's degree with coursework focused on advanced algorithms, mathematics in computing, data structures, etc.
The typical pay range for this role is:$72,100.00 - $158,620.00This 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. The actual base salary offer will depend on a variety of factors including experience, education, geography and other relevant factors. This position is eligible for a CVS Health bonus, commission or short-term incentive program in addition to the base pay range listed above.
In addition to your compensation, enjoy the rewards of an organization that puts our heart into caring for our colleagues and our communities. The Company offers a full range of medical, dental, and vision benefits. Eligible employees may enroll in the Company's 401(k) retirement savings plan, and an Employee Stock Purchase Plan is also available for eligible employees. The Company provides a fully-paid term life insurance plan to eligible employees, and short-term and long term disability benefits. CVS Health also offers numerous well-being programs, education assistance, free development courses, a CVS store discount, and discount programs with participating partners. As for time off, Company employees enjoy Paid Time Off ("PTO") or vacation pay, as well as paid holidays throughout the calendar year. Number of paid holidays, sick time and other time off are provided consistent with relevant state law and Company policies.
For more detailed information on available benefits, please visit Benefits | CVS HealthWe anticipate the application window for this opening will close on: 05/04/2025Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state and local laws.