AI and ML Solution Architect, Singapore

4mo ago, from Hewlett Packard Enterprise

Analyzes, designs, develops and programs integrated software algorithms to structure, analyze, and leverage structured and unstructured data in product and systems applications. Uses large‑scale computing frameworks and data analysis systems to build solutions.

Applies 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. Implements, optimizes, and scales deep learning technologies to enable computers to visualize, learn, and respond to complex scenarios.

Displays technical impact on products or major subcomponents, improves time‑to‑market, achieves cost reductions, and satisfies current and future unmet customer needs. Provides technical leadership for significant projects and mentors junior engineers.

• Develop organization‑wide architectures and methodologies for AI application design and development across multiple platforms and organizations within the Global Business Unit.
• Design, develop, and deploy advanced machine‑learning models and algorithms, including data pre‑processing, feature engineering, model training, and evaluation.
• Stay updated on the latest advancements and lead research initiatives to explore novel approaches and technologies.
• Architect AI systems ensuring scalability, performance, and reliability; optimize algorithms using distributed computing frameworks and cloud services.
• Collaborate with data scientists, software engineers, and product managers to integrate AI into product development.
• Provide technical leadership and mentorship to junior engineers, guiding best practices for AI and machine learning.
• Oversee design review sessions, ensuring consistent design choices and adherence to best practices.
• Partner with engineering managers to establish long‑term design and implementation strategies.
• Lead efforts to incorporate feedback loops and continuous improvement processes.
• Lead meetings, track progress, resolve issues, and coordinate teams.
• Create and deliver high‑level presentations to executive stakeholders, communicating technical strategies and business impact.
• Apply data mining, data modeling, natural language processing, and machine learning to extract and analyze information from datasets.
• May design and develop solutions for complex application problems, system administration issues, or network concerns where applicable.

• Bachelor’s or master’s degree in computer science, engineering, data science, machine learning, artificial intelligence, or a closely related quantitative discipline.
• Typically 10–15 years of experience.

• Deep understanding of supervised, unsupervised, reinforcement learning, deep learning, NLP, computer vision, and statistical modeling.
• Experience implementing and deploying decision trees, random forests, SVMs, neural networks, and familiarity with TensorFlow, PyTorch, or sci‑kit‑learn.
• Expertise in CNNs, RNNs, GANs, and other deep‑learning architectures.
• Strong programming skills in Python, Java, or C++; ability to write clean, efficient, maintainable code.
• Proficient in data wrangling, feature extraction, dimensionality reduction, missing‑value handling, and data‑quality improvement.
• Solid grasp of linear algebra, calculus, probability theory, and statistics.
• Proficiency in data visualization tools to present insights to technical and non‑technical stakeholders.
• Familiarity with software engineering principles, version control (Git), testing methodologies, and agile practices.
• Continuous learning mindset: follows research papers, attends conferences, and contributes to the AI community.
• Experience leading research initiatives, publishing papers, or contributing to open‑source AI projects.
• Experience mentoring and guiding other engineers.
• Strong communication skills for cross‑functional collaboration and stakeholder engagement.

Artificial Intelligence Technologies, Cross Domain Knowledge, Data Engineering, Data Science, Design Thinking, Development Fundamentals, Full Stack Development, IT Performance, Machine Learning Operations, Scalability Testing, Security‑First Mindset

We strive to provide our team members and their loved ones with a comprehensive suite of benefits that supports their physical, financial, and emotional well‑being.

We invest in your career growth and provide programs to help you reach your goals, whether you aim to become a knowledge expert or transition to another division.

We value diverse backgrounds and provide flexibility to manage work and personal needs while fostering an inclusive environment.

HPE is an Equal Employment Opportunity/Veteran/Disabled/LGBT employer. We do not discriminate on the basis of race, gender, or any other protected category, and all decisions are based on qualifications, merit, and business need. HPE complies with all applicable laws related to employer use of arrest and conviction records, including laws requiring consideration of qualified applicants with criminal histories.

Hewlett Packard Enterprise is EEO Protected Veteran/Individual with Disabilities.