About the Job
Aspirature Technology is a leading IT software company dedicated to delivering innovative solutions that transform businesses and enhance user experiences. Our mission is to leverage technology to drive positive change and empower organizations to succeed in the digital age.
The Role
Key Responsibilities
- Design, develop, and implement scalable recommender systems using machine learning algorithms like collaborative filtering, matrix factorization, and deep learning.
- Work closely with cross-functional teams to understand business requirements and translate them into actionable machine learning solutions.
- Perform comprehensive exploratory data analysis to identify relevant features and patterns in large-scale datasets.
- Implement and optimize machine learning models for improved performance, scalability, and efficiency.
- Continuously monitor and evaluate model performance using appropriate metrics and make necessary improvements.
- Document code, methodologies, and experiment results for reproducibility and knowledge sharing.
Ideal Profile
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Engineering, Statistics, or a related field.
- 2 to 3 years of hands-on experience in developing machine learning models, with an emphasis on recommender systems.
- Proficiency in Python programming and familiarity with popular machine learning libraries/frameworks such as TensorFlow, PyTorch, or Scikit-learn.
- Strong understanding of fundamental machine learning concepts, including supervised and unsupervised learning, feature engineering, and model evaluation.
- Experience working with large-scale datasets.
- Excellent analytical and problem-solving skills with a keen attention to detail.
- Strong communication and collaboration skills, with the ability to explain complex technical concepts to non-technical stakeholders.
- Ability to excel in a fast-paced, dynamic environment and adapt to changing priorities.
- Experience with cloud computing platforms such as AWS (including Redshift, Athena, RDS, Spectrum).
Preferred Qualifications
- Familiarity with recommendation system evaluation techniques such as precision, recall, and AUC-ROC.
- Knowledge of natural language processing (NLP) techniques and text-based recommendation systems.
- Contributions to open-source machine learning projects or participation in relevant competitions (e.g., Kaggle) is a plus.
What’s on Offer?
- Bachelor’s or Master’s degree in Computer Science, Engineering, Statistics, or a related field.
- Proficiency in Python programming and popular machine learning libraries/frameworks such as TensorFlow, PyTorch, or Scikit-learn.
- Experience with cloud computing platforms such as AWS (including Redshift, Athena, RDS, Spectrum).