AI and Machine Learning Engineer

Who We Are:

Hewlett Packard Enterprise is the global edge-to-cloud company advancing the way people live and work. We help companies connect, protect, analyze, and act on their data and applications wherever they live, from edge to cloud, so they can turn insights into outcomes at the speed required to thrive in today’s complex world. Our culture thrives on finding new and better ways to accelerate what’s next. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good. If you are looking to stretch and grow your career our culture will embrace you. Open up opportunities with HPE.

Job Description:

At HPE Networking, the Digital Experience & Automation (DEA) team is reimagining how people experience support and services in a digital‑first world—setting new standards for the future of networking. We enable customers, partners, and employees through AI‑driven tools and modern platforms, transforming support into a unified, efficient, and simple experience that drives measurable value. Our mission is grounded in innovation with purpose: applying automation, AI, and data‑driven insights to simplify journeys, reduce friction, and create meaningful outcomes at every touchpoint.

DEA’s charter is to discover, evaluate, and scale solutions that embed intelligent technology into every interaction—delivering proactive and predictive experiences that shorten resolution times and accelerate task completion. We partner closely with technology providers, engineering, and business teams to deliver seamless omnichannel experiences and enable business transformation through data engineering, process optimization, and automation. Our work is fuelled by a passion for self‑service, intelligent automation, and building digital experiences that are intuitive, scalable, and human‑centric.

What you'll do:

Develops and programs integrated software algorithms to structure, analyse and leverage structured and unstructured data in product and systems applications. Can work with large scale computing frameworks, data analysis systems, and modelling environments.

Uses machine learning and statistical modelling 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.

Management Level Definition:

Contributions include applying developed subject matter expertise to solve common and sometimes complex technical problems and recommending alternatives where necessary. Might act as project lead and provide assistance to lower level professionals. Exercises independent judgment and consults with others to determine best method for accomplishing work and achieving objectives.

Responsibilities:

• Responsible for conducting advanced research in AI and machine learning. This includes staying up to date with the latest advancements in the field, exploring emerging technologies, and identifying opportunities to apply cutting-edge techniques to solve complex business problems.
• Tasked with designing and architecting AI solutions for complex problems. This involves analysing business requirements, understanding constraints, and proposing appropriate machine learning models and algorithms.
• Responsible for considering scalability, performance, and maintainability while designing the solution.
• Provides technical guidance and mentorship to junior team members. This includes sharing best practices, reviewing code and designs, and helping team members overcome technical challenges. Participate in technical discussions and provide thought leadership within the organization.
• Works closely with stakeholders, such as product managers, data scientists, and business analysts, to understand their requirements and translate them into technical solutions. Collaborate with cross-functional teams to ensure alignment and successful AI and machine learning project implementation.
• Responsible for driving continuous improvement and innovation in the organization's AI and machine learning practices. This involves identifying areas of improvement, exploring new techniques or technologies, and promoting the adoption of best practices.
• Be involved in evaluating and integrating third-party tools or services that can enhance the capabilities of AI solutions.
• Facilitates design review sessions for your projects, ensuring alignment with project requirements and best practices.
• Mentor junior team members during review sessions.
• Collaborates closely with the engineering manager and team lead to refine and iterating on design and implementation strategies, providing constructive feedback to peers.
• Participates in and coordinates meetings, ensuring effective coordination and communication among team members.
• Independently prepares and delivers detailed presentations and reports to stakeholders, translating complex technical concepts into understandable terms for non-technical audiences.
• May be required to interpret and report data findings and maintain or update specific business intelligence tools, databases, dashboards, systems, or methods
• May be involved in the design and development of solutions to complex application problems, system administration issues, or network concerns, where applicable to the role.

What you need to bring:

• Bachelor's degree in computer science, engineering, data science, machine learning, artificial intelligence, or closely related quantitative discipline. Master’s degree is desirable.
• Typically, 4-9 years’ experience.

Knowledge and Skills:

• Deep understanding of machine learning algorithms, such as linear regression, decision trees, support vector machines, random forests, deep learning models (e.g., neural networks), and reinforcement learning. Proficient in model selection, hyperparameter tuning, and evaluating model performance using appropriate metrics.
• A strong foundation in mathematics and statistics. In-depth knowledge of linear algebra, calculus, probability theory, and statistical concepts. Understanding and developing complex machine learning models and algorithms.
• Proficiency in programming languages such as Python, R, or Java is expected. Experience developing production-level code and familiarity with software engineering best practices, version control systems (e.g., Git), and software development methodologies are also required. Additionally, knowledge of libraries and frameworks like TensorFlow, PyTorch, sci-kit, and Keras is a plus.
• Advanced knowledge and experience in deep learning. Understanding advanced neural network architectures (e.g., convolutional neural networks, recurrent neural networks, transformers) and advanced techniques such as transfer learning, generative models, and optimization algorithms for deep learning.
• Actively staying updated with the latest AI and machine learning research advancements. Experience conducting research, exploring emerging technologies, and identifying opportunities to apply state-of-the-art techniques to solve complex problems.
• Provide technical leadership, mentorship, and guidance to junior team members. Must have excellent communication skills to collaborate with cross-functional teams and stakeholders effectively. Possess strong problem-solving and critical thinking abilities to guide projects, make strategic decisions, and solve complex technical challenges.

What We Can Offer You:

Health & Wellbeing

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

Personal & Professional Development

We also invest in your career because the better you are, the better we all are. We have specific programs catered to helping you reach any career goals you have — whether you want to become a knowledge expert in your field or apply your skills to another division.

Unconditional Inclusion

We are unconditionally inclusive in the way we work and celebrate individual uniqueness. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good.

Let's Stay Connected:

Follow @HPECareers on Instagram to see the latest on people, culture and tech at HPE.

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HPE is an Equal Employment Opportunity/ Veterans/Disabled/LGBT employer. We do not discriminate on the basis of race, gender, or any other protected category, and all decisions we make are made on the basis of qualifications, merit, and business need. Our goal is to be one global team that is representative of our customers, in an inclusive environment where we can continue to innovate and grow together. Please click here: Equal Employment Opportunity.

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

HPE will comply with all applicable laws related to employer use of arrest and conviction records, including laws requiring employers to consider for employment qualified applicants with criminal histories.

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