Tech Stack
AWSAzureCloudCyber SecurityGoogle Cloud PlatformKerasNumpyPandasPythonPyTorchScikit-LearnTensorflow
About the role
- Assist in collecting, cleaning, and preprocessing structured and unstructured data for use in machine learning models.
- Support the design, training, testing, and deployment of machine learning and deep learning models for real-world applications.
- Collaborate with senior engineers and cross-functional teams to identify, extract, and engineer relevant features for model performance.
- Analyze and evaluate model performance using appropriate metrics; help optimize models for accuracy and efficiency.
- Contribute to the integration and deployment of ML models into production environments using APIs or deployment pipelines.
- Stay current with the latest AI/ML trends, tools, and best practices; experiment with innovative techniques under guidance.
- Document datasets, models, experiments, and code to ensure reproducibility and knowledge sharing.
- Communicate technical concepts effectively to both technical and non-technical stakeholders.
Requirements
- Active student working towards a Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, or a related field.
- Proficiency in Python and familiarity with ML libraries such as TensorFlow, PyTorch, Scikit-learn, or Keras.
- Strong understanding of linear algebra, probability, statistics, and optimization techniques.
- Understanding of data manipulation tools (e.g., pandas, NumPy) and data visualization libraries (e.g., Matplotlib, Seaborn).
- Knowledge of version control systems (e.g., Git) for collaborative development.
- Analytical mindset and a passion for solving complex problems.
- Excellent communication and teamwork skills.
- Preferred: Understanding of cloud platforms (AWS, Azure, GCP) and MLOps practices; Familiarity with Agile and DevOps; Exposure to NLP, computer vision, or cybersecurity; Internship or project experience in AI/ML.