GenAI Engineer/Machine Learning Developer

at  EY

GENAI ENGINEER/MACHINE LEARNING DEVELOPER

Let us introduce you the job offer by EY GDS Poland – a member of the global integrated service delivery center network by EY.
EY GDS is a global leader in assurance, tax, transaction, and advisory services. Technology is at the heart of what we do and deliver at EY. Technology solutions are integrated in the client services we deliver and are key to our innovation as an organization.
Fueled by strategic investment in technology and innovation, Client Technology seeks to drive growth opportunities and solve complex business problems for our clients through building a robust platform for business and powerful product engine that are vital to innovation at scale. As part of Client Technology, you’ll work with technologists and business experts, blending EY’s deep industry knowledge and innovative ideas with our platforms, capabilities, and technical expertise. As a catalyst for change and growth, you’ll be at the forefront of integrating emerging technologies from mobile application into every corner of what we do at EY. That means more growth for you, exciting learning opportunities, career choices, and the chance to make a real impact.

SKILLS AND ATTRIBUTES FOR SUCCESS

• 3+ years of experience in ML development and MLOps.
• Strong programming skills, with expertise in languages like Python with a good knowledge of ML, Data and API libraries.
• Expertise in creating end-to-end data pipelines (sourcing, exploration, automation, etc.)
• Experience with ML model and its development.
• Should have knowledge in ModelOps/MLOps, AutoML, AI Ethics, Trust and Explainable AI
• Understanding of some of the popular ML frameworks such as SparkML, Tensorflow, scikit-learn, XGBoost, H2o etc.
• Experience working in a cloud environment (SAP, AWS, Azure, GCP) or a containerized environment (Mesos, Kubernetes)
• Interest in understanding functional and industry business challenges.

• Assist in the collection and documentation of users’ requirements, development of user stories, estimates and work plans
• Ensure modern AI/Gen AI best practices are applied
• Develop, validate and deploy AI models.
• Establish and maintain development standards/best practices
• Analyze the ML algorithms that could be used to solve a given problem and ranking them by their success probability.
• Share the knowledge on the best ML Engineering practices with the team