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Client Technology-AI Developer
Ernst & Young
posted 2mon ago
Job Role Insights
Flexible timing
Key skills for the job
Job Description
- Monitor technology trends and perform RD activities in AI/ML area.
- 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.
- Cooperate with architects to design the system
- Establish and maintain development standards/best practices
- Present effects of work to different stakeholders (e.g., demo)
- 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
- Define validation strategies for ML solutions.
Skills and attributes for success
- 7+ 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.
- Expertise in Big Data, Data Modeling
- Experience working with SAP platforms SAP AI Core, SAP Data Intelligence, Embedded Analytics in S/4HANA or SAP Analytics Cloud
- Exploring and visualizing data to gain an understanding of it, then identifying differences in data distribution that could affect performance when deploying the model in the real world
- Verifying data quality, and/or ensuring it via data cleaning
- Defining data augmentation pipelines
- Training models and tuning their hyperparameters
- Experience in LLMs, LSTM, RNN, Tensorflow, H2O are added advantage
- Experience in deploying AI/ML platforms on Kubernetes and Containerization
- Experience working with large data sets leveraging distributed systems e.g. Spark/Hadoop.
- Experience in managing AI/ML cluster features like API endpoints management, Security, SSO, Auditing, version control, etc
- Good to have (additionally)
- Experience with IBM services for AI/ML (WatsonX, Assistant, Discovery or other)
- A self-starter, independent-thinker, curious and creative person with ambition and passion
Employment Type: Full Time, Permanent
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