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HPE Labs – AI​/ML Engineer III Graduate

Job in Milpitas, Santa Clara County, California, 95035, USA
Listing for: Hewlett Packard Enterprise Development LP
Full Time position
Listed on 2026-02-23
Job specializations:
  • IT/Tech
    AI Engineer, Machine Learning/ ML Engineer, Data Scientist
Salary/Wage Range or Industry Benchmark: 120000 - 150000 USD Yearly USD 120000.00 150000.00 YEAR
Job Description & How to Apply Below
* 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 analyzing 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.
* Bachelor's degree in computer science, engineering, data science, machine learning, artificial intelligence, or closely related quantitative discipline. Master’s degree is desirable.
* Typically, 4-7 years’ experience.
* 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 Tensor Flow, 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…
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