Solution Architect – Generative AI (m/f/d) Full-time

Overview

The Solution Architect forGenerative AI will be part of a team which designs, builds, and operatesthe AI services of Siemens Healthineers (SHS). The ideal candidate for thisrole will have experience with AI services. The role will require the candidateto develop and maintain artificial intelligence systems and applications thathelp businesses and organizations solve complex problems.

The role also requires expertise inmachine learning, deep learning, natural language processing, computer vision,and other AI technologies.

Task and Responsibilities:

SolutionArchitect for Generative AI isresponsible for designing, architecting, and development of AI product/service.The main responsibilities include:

• Designing, developing, and deploying Azure-based AIsolutions, including machine learning models, cognitive services, and dataanalytics solutions.
• Collaborating with cross-functional teams, such as datascientists, business analysts, and developers, to design and implement AIsolutions that meet business requirements.
• Building and training machine learning models using AzureMachine Learning, and tuning models for optimal performance.
• Developing and deploying custom AI models using AzureCognitive Services, such as speech recognition, language understanding, andcomputer vision.
• Creating data pipelines to collect, process, and prepare datafor analysis and modeling using Azure data services, such as Azure Data Factoryand Azure Databricks.
• Implementing data analytics solutions using Azure SynapseAnalytics or other Azure data services.
• Deploying and managing Azure services and resources usingAzure DevOps or other deployment tools.
• Monitoring and troubleshooting deployed solutions to ensureoptimal performance and reliability.
• Ensuring compliance with security and regulatory requirementsrelated to AI solutions.
• Staying up-to-date with the latest Azure AI technologies andindustry developments, and sharing knowledge and best practices with the team.

Qualifications:

• Overall 5+ years’ combined experience in IT and recent 3years as AI engineer.
• Bachelor’s or master’s degree in computer science, informationtechnology, or a related field.
• Experience in designing, developing, and deliveringsuccessful AI Services.
• Experience with cloud computing technologies, such Azure.
• Relevant industry certifications, such as MicrosoftCertified: Azure AI Engineer, Azure Solution Architect etc. is a plus.
• Excellent written and verbal communication skills tocollaborate with cross-functional teams and communicate technical informationto non-technical stakeholders.

Technical skills

• Proficiency in programming languages: You should beproficient in programming language such as Python and R.
• Experience of Azure AI services: You should have experiencewith Azure AI services such as Azure Machine Learning, Azure CognitiveServices, and Azure Databricks.
• Data handling and processing: You should be proficient indata handling and processing techniques such as data cleaning, datanormalization, and feature extraction. Knowledge of SQL, NoSQL, and big datatechnologies such as Hadoop and Spark are also beneficial.
• Experience with Cloud platform: You should have a goodunderstanding of cloud computing concepts and experience working with Azure servicessuch as containers, Kubernetes, Web Apps, Azure Front Door, CDN, WebApplication firewalls etc.
• DevOps and CI/CD: You should be familiar with DevOpspractices and CI/CD pipelines. This includes tools such as Azure DevOps &Git.
• Security and compliance: You should be aware of security andcompliance considerations when building and deploying AI models in the cloud.This includes knowledge of Azure security services, compliance frameworks suchas HIPAA and GDPR, and best practices for securing data and applications in thecloud.
• Machine learning algorithms and frameworks: Knowledge ofmachine learning algorithms and frameworks such as TensorFlow, Keras, PyTorch,and Scikit-learn is a plus.