Software Engineer - Machine Learning

Company:Global Technology organization

Key Skills:

Roles and Responsibilities:

• Design, build, and deploy machine learning models for healthcare applications, including medical image analysis, predictive analytics for patient outcomes, and natural language processing for clinical documents.
• Work with large-scale healthcare datasets such as electronic health records, imaging data, and genomics.
• Pre-process and cleanse healthcare data while ensuring compliance with HIPAA regulations.
• Collaborate with clinicians, data scientists, and software engineers to translate healthcare challenges into scalable ML solutions.
• Research and implement state-of-the-art ML/DL algorithms in the medical AI space.
• Optimize and validate models for fairness, explainability, and robustness.
• Publish findings and contribute to intellectual property, including patents and publications.
• Write clean, maintainable, and efficient code following best practices.
• Participate in code reviews, testing, and debugging.
• Optimize applications for maximum speed and scalability.
• Stay updated with emerging technologies and industry trends.

Skills Required:

• Strong programming expertise in Python and familiarity with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.
• Hands-on experience in Natural Language Processing (NLP) and Deep Learning techniques.
• Experience with MLOps practices -- model deployment, monitoring, and versioning using tools like MLflow, Kubeflow, or Airflow.
• Solid understanding of data preprocessing, data pipelines, and data analysis.
• Knowledge of cloud platforms (AWS, Azure, or GCP) for ML model deployment.
• Familiarity with healthcare data standards (e.g., HL7, FHIR, DICOM) is an advantage.
• Excellent analytical, problem-solving, and communication skills.
• Ability to collaborate effectively in multidisciplinary teams and work in a fast-paced environment.

Education: