Azure AI Solutions Architect
3 weeks ago
About Us:
Fulcrum Digital is a forward-thinking digital company dedicated to pushing the boundaries of innovation in AI. Our Innovation Lab is at the forefront of creating cutting-edge AI solutions that cater to both our internal needs and those of our valued customers.
Role: As an Azure AI 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.
Responsibilities:
- Collaborate with cross-functional teams to understand business requirements and translate them into effective AI solutions.
- Design end-to-end AI architectures, including data pipelines, model training, deployment, and monitoring, using Azure AI services.
- Develop and implement machine learning models and algorithms for various applications, such as image recognition, natural language processing, predictive analytics, and more.
- Write efficient and scalable code to pre-process data, build and train models, and deploy them into production environments.
- Integrate AI solutions with existing systems and applications, ensuring seamless functionality and performance.
- Ensure the security, reliability, and scalability of AI solutions on the Azure platform.
- Provide technical expertise and guidance to team members, fostering a collaborative learning environment.
- Stay up-to-date with the latest advancements in Azure AI services and industry best practices, and apply them to enhance solution offerings.
Requirements:
- Bachelor's or master's degree in computer science, engineering, or a related field.
- Proven experience (7+ 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 Databricks, Azure Cognitive Services, and Azure DevOps.
- Solid understanding of machine learning techniques, algorithms, and best practices for model training and evaluation.
- Experience with data preprocessing, 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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