Role overview
- A Bachelor’s or Master’s degree in Computer Engineering, Data Science, Artificial Intelligence, or a related field.
- 5 years of proven experience developing AI/ML solutions in corporate or consulting environments.
- Strong proficiency in Python, R, or Scala, and experience with frameworks such as TensorFlow, PyTorch, and Scikit-learn.
- Hands-on experience with cloud platforms (Azure, AWS, or GCP) and MLOps best practices.
- Solid understanding of data architecture, APIs, and system integration.
- Excellent communication skills and a results-driven mindset.
- Fluent English (written and spoken).
What we look for
Highly motivated individuals with excellent problem-solving skills and the ability to prioritize shifting workloads in a rapidly changing industry. An effective communicator, you’ll be a confident team player equipped with strong people management skills and a genuine passion to make things happen in a dynamic organization. If you’re ready to take on a wide range of responsibilities and are committed to seeking out new ways to make a difference, this role is for you.
What working at EY offers
EY offers a competitive remuneration package commensurate with your work experience. Plus, we offer:
- Support, coaching and feedback from some of the most engaging colleagues around.
- Opportunities to develop new skills and progress your career.
- The freedom and flexibility to handle your role in a way that’s right for you.
*The exceptional EY experience. It’s yours to build.
What we look for**
Highly motivated individuals with excellent problem-solving skills and the ability to prioritize shifting workloads in a rapidly changing industry. An effective communicator, you’ll be a confident team player equipped with strong people management skills and a genuine passion to make things happen in a dynamic organization. If you’re ready to take on a wide range of responsibilities and are committed to seeking out new ways to make a difference, this role is for you.
What you'll work on
- Deploy and productionize AI models into scalable environments.
- Integrate AI solutions with enterprise systems and workflows.
- Optimize model performance for speed, accuracy, and reliability.
- Implement security and compliance standards in AI deployments.
- Collaborate with MLOps and data engineering teams for seamless delivery.