Role Overview: The Machine Learning Specialist designs, builds, and deploys scalable Machine Learning (ML) models to solve complex business problems. You will work at the intersection of data science and software engineering to transform raw data into predictive intelligence.
Key Responsibilities
- Model Development: Design and train ML models (Regression, Classification, Clustering, and NLP).
- Data Engineering: Perform data discovery, cleaning, and feature engineering to prepare high-quality datasets.
- Deployment (MLOps): Integrate models into production environments and monitor performance for “drift” or accuracy loss.
- Optimization: Fine-tune hyperparameters and optimize algorithms for speed and scalability.
- Collaboration: Work with Data Engineers and Product Managers to align AI solutions with business goals.
Core Requirements
- Technical Stack: Proficiency in Python or R; experience with frameworks like PyTorch, TensorFlow, or Scikit-learn.
- Math Foundation: Strong understanding of linear algebra, calculus, and statistics.
- Cloud Platforms: Familiarity with AWS (SageMaker), Google Cloud (Vertex AI), or Azure ML.
- Education: Degree in Computer Science, Data Science, Statistics, or a related field.
