Machine Learning Engineer

About the Role

Key Responsibilities

• Design, develop, and deploy machine learning models and pipelines for classification, regression, clustering, and recommendation systems.
• Collaborate with cross-functional teams to understand business requirements and translate them into ML solutions.
• Conduct data preprocessing, feature engineering, and model evaluation using statistical and ML techniques.
• Implement and optimize ML algorithms using frameworks such as TensorFlow, PyTorch, Scikit-learn, and XGBoost.
• Monitor model performance and retrain models as needed to ensure accuracy and relevance over time.
• Maintain and scale ML infrastructure, ensuring high availability and performance.
• Document processes, models, and experiments for reproducibility and compliance.
• Stay current with the latest research and advancements in machine learning and AI.

Requirements

• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related field.
• 3+ years of experience in machine learning, data science, or AI engineering.
• Proficiency in Python and ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch).
• Strong understanding of statistics, linear algebra, and probability theory.
• Experience with cloud platforms (e.g., Azure, AWS, GCP) and MLOps tools.
• Familiarity with data versioning, model deployment, and monitoring best practices.

Nice to Have

• Experience with NLP, computer vision, or time-series forecasting.
• Knowledge of data governance, model explainability, and ethical AI practices.
• Exposure to tools like MLflow, Kubeflow, or SageMaker.

Benefits & Perks

• Medical, dental, vision, PTO, and holidays.