Hewlett Packard Enterprise is looking to advance the way people live and work by connecting, protecting, analyzing, and acting on their data and applications from edge to cloud, and this role is designed to contribute to this goal by designing, developing, and implementing AI and machine learning models.
Requirements
- 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.
- Bachelor's degree in computer science, engineering, data science, machine learning, artificial intelligence, or closely related quantitative discipline.
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.
Other
- Bachelor's 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.
- Must be able to work on average 2 days per week from an HPE office.
- Must be able to attend 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.
- Must be able to prepare and deliver detailed presentations and reports to stakeholders as directed by the engineering manager and team lead.
