AI and Machine Learning Engineer
hpe
Job Description
- 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.