Note: The job is a remote job and is open to candidates in USA. EY is a globally connected powerhouse of diverse teams dedicated to building a better working world. The CT_NITRO Experimental AI Engineer will lead the design and deployment of generative AI models, oversee the data science lifecycle, and mentor junior data scientists while integrating AI insights into products and services.
Responsibilities
- Leads the design, development, and deployment of advanced generative AI models, including large language models (LLMs), driving innovation and solving complex business challenges
- Oversees the end-to-end data science lifecycle, from data acquisition and preprocessing to model validation and optimization, ensuring best practices and high-quality outcomes
- Works on developing and deploying machine learning algorithms, ensuring models are optimized for performance and scalability
- Mentors and guides junior data scientists, fostering a collaborative environment and promoting knowledge sharing of cutting-edge techniques and tools
- Partners with cross-functional teams to integrate AI-driven insights into products and services, translating sophisticated models into practical, scalable solutions that drive measurable impact
- Implementing AI solutions that integrate seamlessly with existing business systems to enhance functionality and user interaction
- Reviewing complex data sets to establish data quality and highlighting where data cleansing is required to remediate the data
- Designing and implementing data models to manage data within the organization
- Migrating data from one system to another using multiple sources, identifying and implementing storage requirements
- Analyzing the latest trends such as cloud computing and distributed processing, and their uses in business, building industry knowledge
- Peer reviewing models and working with relevant business areas to seek their input and ensuring they are fit for the designed purpose
- Automating important infrastructure for the data science team
- Staying current with AI trends and suggesting improvements to existing systems and workflows
Skills
- 8+ years' experience in machine learning, large scale data acquisition, transformation, and cleaning, both structured and unstructured data
- Experience with generative LLM fine-tuning and prompt engineering
- Proficiency with data wrangling, visualization, and modeling in Python
- Experience in ML/NLP algorithms, including supervised and unsupervised learning
- Experience in machine learning frameworks and tools (e.g., sci-kit-learn, Keras, TensorFlow, MXNet, PyTorch, MLlib)
- Strong programming skills in Python
- Experience with SQL, Document DBs and Vector DBs
- Batch Processing - Capability to design an efficient way of processing high volumes of data where a group of transactions is collected over a period Data
- Visualization and storytelling - Capability to assimilate and present data, as well as more advanced visualization techniques. Capability to engage and explain data creating a narrative around data visualization
- Experience with Git and modern software development workflow
- Strong team and business communication skills – can walk through and approach with technical clients or explain tricky concepts to non-technical people
- Must thrive in a fast-paced environment and be able to work independently
- Excellent in communication skills
- Strong analytical skills and problem-solving ability
- A self-starter, independent-thinker, curious and creative person with ambition and passion
- Excellent inter-personal, communication, collaboration, and presentation skills
- Customer focused
- Excellent time management skills
- Positive and constructive minded
- Takes responsibility for continuous self-learning
- Takes the lead and makes decisions in critical times and tough circumstances
- Attention to detail
- High levels of integrity and honesty
- Good knowledge with cloud ecosystems, Azure is preferred
- Experience with tools in the distributed computing, GPU, cloud platforms, and Big Data domains (e.g., GCP, AWS, MS Azure, Hadoop, Spark, Databricks) is a plus
- Knowledge of containerization platforms like Docker is a plus
- Education: Bachelor/Master/PG in Artificial Intelligence, Analytics, Data Science, Computer Science, Engineering, Information Technology, Social Sciences or related fields preferred
Benefits
- Comprehensive compensation and benefits package
- Base salary range for this job in all geographic locations in the US is $92,600 to $173,100.
- Medical and dental coverage
- Pension and 401(k) plans
- A wide range of paid time off options
- Join us in our team-led and leader-enabled hybrid model. Our expectation is for most people in external, client serving roles to work together in person 40-60% of the time over the course of an engagement, project or year.
- Under our flexible vacation policy, you’ll decide how much vacation time you need based on your own personal circumstances.
- You’ll also be granted time off for designated EY Paid Holidays, Winter/Summer breaks, Personal/Family Care, and other leaves of absence when needed to support your physical, financial, and emotional well-being.
Company Overview
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