Machine Learning Engineer (Mid-Senior Level)

Client of Business Alliance HR Services

Job Summary:

We are looking for a Machine Learning Developer who is passionate about healthcare and experienced in working with medical data. The ideal candidate has practical experience in building, fine-tuning, and deploying deep learning models for large-scale data. The role involves working with key healthcare stakeholders in the region, handling large-scale medical records and healthcare transactional data. It also includes research, data analysis, forecasting, and interpretation of results.

Essential Duties and Responsibilities:

• Develop and maintain healthcare calculators and simulations using ML and data-driven techniques.
• Perform data wrangling, preprocessing, and analysis on various healthcare datasets to ensure data quality and usability.
• Design, implement, and evaluate machine learning and deep learning models for predictive analytics and decision support in healthcare.
• Conduct train-test split and model training to optimize performance and generalizability.
• Collaborate with healthcare stakeholders to gather requirements, design solutions, and implement AI and data-driven applications.
• Ensure data management best practices, including data governance, data security, and data privacy, are followed.
• Utilize SQL for data extraction, transformation, and loading (ETL) processes.
• Continuously monitor and refine models and algorithms to improve accuracy and efficiency.
• Stay current with the latest advancements in machine learning, and data science, and apply these advancements to healthcare applications.
• Conduct research, data analysis, forecasting, and interpretation of results.
• Deal with data preprocessing, including handling missing values, data cleaning, normalization, and transformation.
• Implement strategies for data imputation and dealing with outliers.
• Optimize data pipelines to ensure efficient data processing and storage.
• Work with large-scale datasets, ensuring data integrity and consistency.

Requirements

• Good theoretical understanding of machine learning & deep learning principles and various statistical techniques and evaluation techniques.
• Knowledge of basic algorithms, object-oriented and functional design principles, and best practice patterns.
• Experience in developing and fine-tuning machine learning models considering healthcare-specific problems.
• Experience in benchmarking and model performance evaluation and improvement.
• Familiarity with APIs and SDKs for real-time model deployment.
• Experience in using frameworks such as MLflow, Kubeflow, Airflow, Seldon Core, TFServing.
• Proven experience in using Python, Scikit-Learn, PyTorch, Polars, and Pandas.
• Knowledge and experience in using SQL and performing queries in large-scale databases.
• Basic knowledge in data visualization and results representation.
• Experience working with developer tools such as PyCharm/MS Visual Studio, Docker, etc.
• Experience in working and building models for time-series data.
• Familiarity with REST API development, NoSQL design, RDBMS design and optimizations, and cloud environments.
• Familiarity with working on remote and virtual machines.
• Familiarity with distributed training and performance optimization on GPUs is a plus.