AI and Machine Learning Engineer

About this role

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AI and Machine Learning Engineer

HPE

In OfficeBengaluru

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Skills you'll use

What you'll do

• 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.

Who can apply

• 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.

About HPE

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