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Azure ML Architect

2 months ago

Santa Clara, United States Ehub Global Inc Full time

Experience on Data Bricks Development platform Prior Experience Hands on experience on working in Azure. cloud platform

Experience in designing and implementing scalable and secure Azure cloud solutions using Data Bricks ML platform.

Understanding of implementation of architecture within Azure Big Data Analytics Al tools.

Expert level in Designing and Architect solutions in Azure Data factory, Azure Databricks, Azure Datalake, Delta Lake and Azure synapse analytics implementation.

Experience in Azure cloud technologies like PySpark, Synapse, ADF, Databricks, Python, Scala and SQL.

Have good experience configuring Microservices using Docker, Kubernetes on Azure Data Bricks

Extensive Experience on working on Azure AI services including Data Bricks and Azure cognitive services.

Highly preferred experience on working with Azure OpenAI services.

Hands-on experience on design, and optimizing LLM, natural language processing (NLP) systems, frameworks, and tools.

Hands-on AI/ML modeling experience of complex datasets combined with a strong understanding of the theoretical foundations of AI/ML.

Expertise in most of the following areas: supervised & unsupervised learning, deep learning, reinforcement learning, federated learning, time series forecasting, Bayesian statistics, and optimization. Experience in creating and deploying code libraries using functions and classes in Python in AI product-focused development. Well-versed in software development and code quality best industry practices. Experience working with Agile Development methodologies.


Responsibilities:

Your primary responsibility is to Architect, design and develop AI application on Azure cloud.

Lead the azure cloud architecture design for various applications depending on business requirements.

Prototypes and do proof of concepts (PoC) in one or all the following areas: LLM, NLP, DL (Deep Learning), ML (Machine Learning), object detection/classification, tracking, etc.

Stay up to date with the latest advancements in LLM, NLP, deep learning, machine learning, and object detection algorithms, and proactively identify opportunities to leverage new technologies for improved solutions. You will work with a team of researchers and engineers to build state-of-the-art language models that can understand and generate human-like text.

Work with business users to translate functional requirements into data specifications Collaborate with data scientists and business users to transform domain know-how into functional requirements.

Data Analysis and Preprocessing:

Collect and preprocess large-scale text corpora to train and fine-tune language models.

Conduct data analysis to identify patterns, trends, and insights that can inform model development and improvement.