Machine Learning Engineer

CVS Health, the parent company of Signify Health, is increasing investments in digital, data, analytics and technology and Signify Health is excited to be involved
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.
CVS Health is focused on driving business agility and growth through technology, data, digital and experiential innovations.
'Digital First, Technology Forward and Data Driven' is not simply an aspirational goal for the company, but a prerequisite to accelerated growth.
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.
As we reflect on our learnings and successes from remote work, we aim to provide a new state of the art flexible work environment in our Galway facility at Bonham Quay to support those objectives.
Careers with offer flexible work arrangements and individuals who live and work in the Republic of Ireland will have the opportunity to divide their time between our Galway office and their home office.
Position Summary The 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.
The ML Engineer will actively collaborate with Data Scientists to successfully optimize, and scale complex ML models & optimizer solvers that enable highly dynamic & sophisticated pricing and promotion strategies.
The incumbent in this role will have the opportunity to work on challenging business problems leveraging cutting-edge technologies including Big Data, Distributed Computing, and Machine learning.
Key job duties include: Partner with data scientists to train, optimize, scale and support AI/ML models.
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.
Required Qualifications: 3+ years professional experience in implementing ML and Data Engineering at scale.
3+ years of experience with Python & SQL programming language.
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 of experience in building cloud native analytical solutions, either on Azure or GCP.
1+ years designing, implementing, and optimizing machine learning algorithms and models using open-source machine learning frameworks such as TensorFlow, PyTorch, and XGBoost.
1+ years' experience in end-to-end ML implementation lifecycle including feature engineering, training, inference, model drift measurement, and model observability.
1+ 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.
Experience in deploying supervised machine learning, time series modeling, CNNs, ensemble models.
Exposure to deploying ML optimization models such as Pyomo/ IPOPT.
Exposure in implementing Gen AI and/or NLP based solutions using LLMs.
Education: Bachelor's degree in computer science or equivalent.
Master's degree preferred.
To Apply Please forward your CV via the APPLY Now button below.