AI and ML Solution Architect - Central Region

Only for registered members Central Region, Singapore

1 month ago

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AI solution Architect at Hewlett Packard Enterprise Job Description - Analyzes designs develops programs integrated software algorithms structure analyze leverage structured unstructured data product systems applications Uses machine learning statistical modeling techniques improve performance data management quality accuracy Formulates descriptive diagnostic predictive prescriptive insights algorithms translates technical specifications code Applies optimizes scales deep learning technologies algorithms give computers visualize learn respond complex situations Documents procedures installation maintenance completes programming performs testing debugging defines monitors performance metrics Contributes success HPE translating customer requirements industry trends AI ML products solutions systems improvement projects Responsibilities Develops organization-wide architectures methodologies AI applications design development multiple platforms organizations Global Business Unit Responsible designing developing deploying advanced machine learning models algorithms Selecting appropriate techniques pre-processing feature engineering model training evaluation Stays date latest advancements field leads research initiatives explore novel approaches technologies Conducting experiments evaluating new algorithms identifying opportunities innovation Responible designing architecture AI systems ensuring scalability performance reliability Optimizing algorithm leveraging distributed computing frameworks utilizing cloud services enable efficient effective AI solutions Works closely other teams data scientists software engineers product managers Collaborate understand requirements identify opportunities integration provide technical guidance development process Provides technical leadership mentorship junior engineers guiding best practices review feedback help grow improve skills Oversees guides multiple design review sessions different projects ensuring consistency design choices adherence best practices Act key mentor team Partners engineering manager lead establish long-term design implementation strategies Leads efforts incorporate feedback loops continuous improvement processes Leads meetings efficient progress tracking issue resolution team coordination Support engineer manager setting meeting agendas Creates delivers high-level presentations reports executive stakeholders effectively communicating complex technical strategies impact business goals Applies leverages data mining modeling natural language processing extract analyze information datasets May involved design development solutions complex applications problems system administration issues network concerns applicable role Education Experience Required Bachelor master degree computer science engineering data science machine learning artificial intelligence quantitative discipline Typically years experience Knowledge Skills Solid understanding fundamental concepts including supervised unsupervised learning deep reinforcement natural language vision statistical modeling Proficient implementing deploying various machine learning algorithms decision trees random forests support vector machines neural networks Knowledge popular frameworks libraries TensorFlow PyTorch sci-kit highly valuable Expertise deep techniques architectures frameworks convolutional recurrent generative adversarial networks etc Strong programming skills necessary implementing deploying models Proficiency Python Java C++ required Ability write clean efficient maintainable code knowledge software engineering best practices Skilled preparing cleaning data tasks which include wrangling extraction dimensionality reduction handling missing values addressing quality issues Solid understanding mathematical concepts linear algebra calculus probability theory statistics crucial designing evaluating models Proficiency visualization tools techniques analyze present insights gained from ML Models Create meaningful visualizations communicate complex concepts technical non-technical stakeholders Familiarity software engineering principles version control systems Git testing methodologies agile development practices valuable robustness scalability maintainability
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