Azure Artificial Intelligence Solution Architect
6 days ago
Role : Azure AI Solution Architect (Preferred Data Science Profiles)
Experience : 8+ Years
Location : Pune (Hybrid)
Joy Type : Permanent
Notice period : immediate to 20 days ( max)
The Role :
As an Azure AI implementer and Solutions Architect, you will be responsible for designing, developing, and deploying AI solutions on the Azure platform to meet the diverse needs of our organization and clients.
Mandatory Skills : Azure, Python, TensorFlow, PyTorch, scikit-learn, AI, ML, LLM
Roles & Responsibilities :
- Collaborating with cross-functional teams to understand business requirements and translate them into effective AI solutions.
- Designing end-to-end AI architectures, including data pipelines, model training, deployment, and monitoring, using Azure AI services.
- Developing and implementing machine learning models and algorithms for various applications, such as image recognition, natural language processing, predictive analytics, and more.
- Writing efficient and scalable code to pre-process data, build and train models, and deploy them into production environments.
- Integrating AI solutions with existing systems and applications, ensuring seamless functionality and performance.
- Ensuring the security, reliability, and scalability of AI solutions on the Azure platform.
- Providing technical expertise and guidance to team members, fostering a collaborative learning environment.
- Staying up to date with the latest advancements in Azure AI services and industry best practices, and applying them to enhance solution :
- Bachelor's or master's degree in Computer Science, Engineering, or a related field.
- Proven experience (7-8+ years) designing, developing, and deploying AI solutions in the Azure environment.
- Strong proficiency in programming languages such as Python, and familiarity with relevant libraries and frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
- Hands-on experience with Azure AI services, including Azure Machine Learning, Azure Data bricks, Azure Cognitive Services, and Azure DevOps.
- Solid understanding of machine learning techniques, algorithms, and best practices for model training and evaluation.
- Experience with data pre-processing, feature engineering, and working with structured and unstructured data.
- Ability to optimize and fine-tune models for performance, scalability, and resource efficiency.
- Excellent problem-solving skills and the ability to troubleshoot complex technical issues.
- Strong communication and collaboration skills, with the ability to work effectively in a cross-functional team environment.
- Experience in deploying AI models as APIs or microservices is a plus.
- Relevant certifications in Azure AI and machine learning are highly desirable.
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