Job Description
We are hiring for a dynamic new initiative for CVS Health that will run out of our state-of-the-art offices at Bonham Quay.
This is your opportunity to be involved with a pioneering business that is transforming health care in the United States by making customer experiences more seamless, convenient and personalised.
Our Purpose
At CVS Health, we share a single, clear purpose: Bringing our heart to every moment of your health.
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.
The Role
The Sr. ML Engineer, part of the broader Retail Analytics Engineering department, supports the Price Value & Assortment Analytics organization in the development of AI/ML driven analytical solutions at scale.
Key Responsibilities
* Partner with data scientists to train, optimize, scale and support AI/ML models.
* Establish robust Data and ML engineering principles in the implementation of ML algorithms on the Azure Kubernetes or Google Cloud platform.
* Translating functionality into scalable, tested, and configurable platform architecture and software.
* Ensure models are integrated into production systems with high reliability and performance.
* Design and conduct experiments to evaluate the performance of machine learning models.
* Iterate on models based on feedback and evolving business requirements.
* Build frameworks, reusable modules, and author best practices and standards to enable self-serve capabilities that enable data scientists to deploy solutions quickly and efficiently.
Requirements
* 5+ years professional experience in implementing ML and Data Engineering at scale.
* 5+ years of experience with Python & SQL programming language.
* 5+ years of experience in building cloud native analytical solutions, either on Azure or GCP.
* 3+ years designing, implementing, and optimizing machine learning algorithms and models using open-source machine learning frameworks such as TensorFlow, PyTorch, and XGBoost.
* 3+ years' experience in end-to-end ML implementation lifecycle including feature engineering, training, inference, model drift measurement, and model observability.
* 3+ years' experience with working in Dev/ML Ops model and industry deployment best practices using CI/CD tools and infrastructure as a code (e.g., Jenkins, Docker, Kubernetes).
* 3+ years' experience in building data engineering pipelines, and metric aggregation layers.
Preferred Qualifications
* Experience working in Retail domain with a strong functional understanding of product pricing and promotion strategies is a plus.
* Experience in Google Cloud platform, including Big Query, Vertex AI.
* Hands-on experience working in scalable distributed computation frameworks like Spark or Dask.
* Expertise with working with open-source ML platforms & toolsets such as Kubeflow, Airflow and Feast is preferred.
Education
* Bachelor's degree in computer science or equivalent.
* Master's degree preferred.