Al And ML Solution Architect

Analyzes, designs, develops and programs integrated software algorithms to structure, analyze and leverage structured and unstructured data in product and systems applications. Can work with large scale computing frameworks, data analysis systems, and modeling environments. Uses machine learning and statistical modeling techniques to improve product/system performance, data management, quality, and accuracy. Formulates descriptive, diagnostic, predictive and prescriptive insights/algorithms and translates technical specifications into code. Applies, optimizes and scales deep learning technologies and algorithms to give computers the capability to visualize, learn and respond to complex situations. Documents procedures for installation and maintenance, completes programming, performs testing and debugging, defines and monitors performance metrics. Contributes to the success of HPE by translating customer requirements and industry trends into AI/ML products, solutions, and systems improvement projects. Contributions have visible technical impact on a product or major subcomponent. Applies in-depth professional knowledge and innovative ideas to solve complex problems. Visible contributions improve time-to-market, achieve cost reductions, or satisfy current and future unmet customer needs. Recognized internal authority on key technology area applying innovative principles and ideas. Provides technical leadership for significant project/program work. Leads or participates in cross-functional initiatives and contributes to mentorship and knowledge sharing across the organization. Responsibilities: Develops organization-wide architectures and methodologies for AI applications design and development across multiple platforms and organizations within the Global Business Unit. Responsible for designing, developing, and deploying advanced machine learning models and algorithms. This includes selecting appropriate techniques, data pre-processing, feature engineering, model training, and evaluation. Stays up to date with the latest advancements in the field and leads research initiatives to explore novel approaches and technologies. This involves conducting experiments, evaluating new algorithms, and identifying opportunities for innovation. Responsible for designing the architecture of AI systems and ensuring scalability, performance, and reliability. This includes optimizing algorithms, leveraging distributed computing frameworks, and utilizing cloud services to enable efficient and effective AI solutions. Works closely with other teams, such as data scientists, software engineers, and product managers. You will collaborate to understand requirements, identify opportunities for AI integration, and provide technical guidance throughout the development process. Provides technical leadership and mentorship to junior engineers, guiding them in best practices for AI and machine learning. Review their work and provide feedback to help them grow and improve their skills. Oversees and guides multiple design review sessions across different projects, ensuring consistency in design choices and adherence to best practices. Act as a key mentor for the team. Partners with the engineering manager and team lead to establish long-term design and implementation strategies. Leads efforts to incorporate feedback loops and continuous improvement processes. Leads meetings, ensuring efficient progress tracking, issue resolution, and team coordination. Support the engineering manager in setting meeting agendas. Creates and delivers high-level presentations and reports to executive stakeholders, effectively communicating complex technical strategies and their impact on business goals. Applies and leverages data mining, data modeling, natural language processing, and machine learning to extract and analyze information from datasets May be involved in the design and development of solutions to complex applications problems, system administration issues, or network concerns, where applicable to the role. Education and Experience Required: Bachelor's or master’s degree in computer science, engineering, data science, machine learning, artificial intelligence, or closely related quantitative discipline. Typically, 10-15 years’ experience. Knowledge and Skills: Solid understanding of fundamental AI and machine learning concepts, including supervised and unsupervised learning, deep learning, reinforcement learning, natural language processing, computer vis…