Job Description

EY GDS is actively recruiting an accomplished AI Engineer to join our dynamic innovation-driven team. We are looking for an expert with rich experience in deploying machine learning models and using Azure IA services. The successful candidate will work closely with data science and is anticipated to bring about a consultancy mindset, demonstrating flexibility in adopting new technologies.

As an AI Engineer at EY GDS, you will not only collaborate with data scientists but also work closely with data analysts and data engineers, forming a multi-disciplinary team that pushes the boundaries of what's possible.

Responsibilities:

• Design, develop, and deploy machine learning models addressing our business needs.
• Utilize Cloud based AI services (Azure, GCP, AWS, Databricks) and Gen AI to develop intelligent AI solutions and GenAI Agents.
• Build AI applications suitable for both on-premises and cloud environments.
• Streamline efficient data pipelines for data ingestion, processing, and the deployment of production models.
• Collaborate with Data Scientists to effectively transform prototypes into scalable software solutions.
• Work with Data Analysts and Data Engineers to ensure optimal data use and efficient resource allocation.
• Stay on top of the latest AI technologies and implement them to continually improve our solutions.

Desired Experience:

• A Minimum of 3 years of experience as an AI or Machine Learning Engineer or similar role.
• Proven experience deploying machine learning models and managing data science pipelines.
• Hands-on experience with Cloud AI services and Gen AI (Azure, AWS, Databricks, GCP)
• A track record of developing, implementing, and maintaining AI solutions in a business context.
• Proven experience working within a multidisciplinary team of Data Scientists, Analysts, and Data Engineers.

Requirements:

• A bachelor's or master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
• Strong proficiency in Python, with an in-depth knowledge of libraries like Numpy, Scikit-learn, TensorFlow, or PyTorch.
• Demonstrable understanding of machine learning algorithms, principles, and their real-world application.
• Understanding of data structures, data modeling and software architecture.

Soft Skills:

• Excellent communication skills, both written and verbal.
• A consulting mindset with the capacity and enthusiasm to learn and implement new technologies.
• A resilient mind to overcome every challenge that might arise in different types of projects.
• Familiarity with agile/scrum methodology and software development life cycle principles.
• Ability to easily communicate complex AI concepts to non-tech business leaders
• Candidate should keep informed and research about the latest trends in AI/ML topics as this field is constantly evolving.