Basic Qualifications
Bachelors degree in relevant discipline (Computer Science, Engineering, IT, Information Systems or a related field, or equivalent experience)
- Bachelors degree in computer science, Engineering, or related field.
- 4+ years of professional experience as a Python Developer or Software Engineer.
- 1+ year of experience or strong exposure with cloud computing platforms, particularly AWS
- Strong proficiency in Python programming language and related frameworks/libraries.
- Experience with machine learning techniques and frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
- Familiarity with AWS services such as EC2, S3, Lambda, SageMaker, Comprehend and CloudFormation.
- Solid understanding of software engineering principles, algorithms, and data structures.
- Excellent problem-solving skills and ability to work in a fast-paced environment.
- Strong communication and collaboration skills, with the ability to work effectively in a team environment.
Roles & Responsibilities:
- Collaborate with cross-functional teams to define machine learning requirements and develop scalable solutions.
- Design and implement machine learning models and algorithms using Python libraries such as TensorFlow, PyTorch, or scikit-learn.
- Develop and maintain data processing pipelines for feature engineering, model training, and evaluation.
- Deploy machine learning models into production environments on AWS cloud infrastructure.
- Utilize AWS services such as EC2, S3, Lambda, and SageMaker to build and deploy scalable solutions.
- Implement monitoring and logging mechanisms to track model performance and system health.
- Optimize machine learning workflows for performance, scalability, and cost-effectiveness.
- Stay updated on the latest advancements in machine learning techniques, AWS services, and best practices.
- Participate in code reviews, pair programming, and knowledge-sharing sessions with team members.
Nice to have:
- US Healthcare knowledge is an advantage.
- Experience with containerization technologies such as Docker and Kubernetes.
- Knowledge of DevOps practices and tools for CI/CD automation.
- Familiarity with SQL databases and big data technologies (e.g., Hadoop, Apache Spark).
