Machine Learning Engineer - Python

Responsibilities :

- Design, develop, and implement machine learning models and algorithms for various applications (e.g., classification, regression, natural language processing, computer vision).

- Build and maintain scalable data pipelines for data ingestion, preprocessing, feature engineering, and model training.

- Evaluate model performance using appropriate metrics and statistical methods.

- Optimize models for accuracy, efficiency, and scalability.

- Deploy machine learning models into production environments using appropriate deployment frameworks and tools.

- Develop and maintain monitoring systems to track model performance and identify potential issues.

- Collaborate with data scientists to understand business problems and translate them into machine learning solutions.

- Work closely with software engineers to integrate machine learning models into existing applications and infrastructure.

- Stay up-to-date with the latest advancements in machine learning, deep learning, and related technologies.

- Contribute to the development of best practices and standards for machine learning engineering.

- Document machine learning workflows, models, and deployment processes.

Required Skills :

- Bachelor's or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, Statistics, or a related quantitative field.

- 2+ years of professional experience as a Machine Learning Engineer or a similar role.

- Strong understanding of machine learning algorithms and concepts.

- Proficiency in Python and relevant machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch, Keras).

- Experience in building and deploying machine learning models.

- Experience with data preprocessing, feature engineering, and data visualization techniques.

- Familiarity with cloud computing platforms (e.g., AWS, Azure, GCP) and their machine learning services.

- Experience with data pipeline tools and technologies (e.g., Apache Spark, Apache Kafka, Airflow).

- Strong problem-solving and analytical skills.

- Excellent communication and collaboration skills.

- Experience with version control systems (e.g., Git).

Preferred Skills:

- Experience with deep learning frameworks and techniques.

- Familiarity with MLOps principles and tools for model deployment and monitoring.

- Experience with containerization technologies (Docker, Kubernetes).

- Knowledge of big data technologies and distributed computing.

- Experience with specific machine learning domains (e.g., NLP, computer vision, recommender systems).

- Contributions to open-source machine learning projects.

- Experience with A/B testing and model evaluation in production