AI/ML Engineer @ Hewlett Packard

AI/ML Engineer

This role has been designed as Onsite with an expectation that you will primarily work from an HPE office.

Job Family Definition:

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.

Management Level Definition:

Contributes to assignments of limited scope by applying technical concepts and theoretical knowledge acquired through specialized training, education, or previous experience. Acts as team member by providing information, analysis and recommendations in support of team efforts. Exercises independent judgment within defined parameters.

Responsibilities:

• Designs, develops and implements AI and machine learning models. This includes data pre-processing, feature engineering, algorithm selection, model training, and evaluation.
• Gathers and analyzes relevant data sets to train and test machine learning (ML) models. Understands data analysis techniques, statistical methods, and data visualization to gain insights from the data and make informed decisions.
• Optimizing algorithms and models to improve their performance is an essential responsibility for AI and Machine Learning Engineers. This involves fine-tuning hyperparameters, conducting experiments, implementing optimization techniques, and employing feature selection or dimensionality reduction methods.
• Works closely with cross-functional teams, including data scientists, software engineers, product managers, and domain experts. Collaboration is crucial for understanding project requirements, aligning objectives, and integrating AI/ML solutions into existing systems or products.
• Keeping accurate and up-to-date AI and machine learning project documentation. Document work, including methodologies, code, and experimental results. Responsible for preparing reports and presenting findings or recommendations to stakeholders.
• Participates in regular design review sessions with the engineering manager, team leader, and other stakeholders to ensure that design choices align with project requirements and best practices.
• Actively seeks and incorporates feedback from the engineering manager or team leader during the design and implementation phases to ensure continuous improvement and adherence to project goals.
• Attends daily or weekly stand-up meetings led by the engineering manager or team lead providing updates on progress, discuss challenges, and coordinate efforts with other team members.
• Prepares and delivers detailed presentations and reports to stakeholders as directed by the engineering manager and team lead, ensuring that complex technical information is communicated clearly and effectively.
• May be required to interpret and report data findings and maintain or update specific business intelligence tools, databases, dashboards, systems, or methods.

Education and Experience Required:

• Bachelors degree in computer science, engineering, data science, machine learning, artificial intelligence, or closely related quantitative discipline. Master s degree is desirable.
• Typically, 0-2 years experience.

Knowledge and Skills:

• Proficiency in programming languages such as Python, R, or Java is required. Knowledge of libraries and frameworks commonly used in AI and machine learning, such as TensorFlow, PyTorch, or scikit-learn, is highly beneficial.
• A solid understanding of statistics, probability, linear algebra, calculus, and optimization methods is crucial for building and evaluating machine learning models.
• In-depth knowledge of machine learning algorithms, techniques, and concepts is essential. This includes supervised and unsupervised learning, deep learning, neural networks, reinforcement learning, and natural language processing.
• Proficiency in working with large datasets, data pre-processing, data cleaning, and exploratory data analysis is necessary. Experience with SQL and databases and data visualization tools like Matplotlib or Tableau is required.

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

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.

Job:

Engineering

Job Level:

TCP_01

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