GE HealthCare Staff Software Engineer 

India, Karnataka 

161786751

As a Staff Software Engineer, you will play a crucial role in bridging the gap between data science and production, ensuring the seamless integration and deployment of machine learning models into operational systems. You will be responsible for designing, implementing, and managing the infrastructure and workflows necessary to deploy, monitor, and maintain machine learning models at scale.

Responsibilities:

Infrastructure Design and Maintenance:Design, build, and maintain scalable and robust infrastructure for model deployment, monitoring, and management. This includes containerization, orchestration, and automation of deployment pipelines.

Continuous Integration/Continuous Deployment (CI/CD):Implement and manage CI/CD pipelines for automated model training, testing, and deployment.

Model Monitoring and Performance Optimization:Develop monitoring and alerting systems to track the performance of deployed models and identify anomalies or degradation in real-time. Implement strategies for model retraining and optimization.

Data Management and Version Control:Establish processes and tools for managing data pipelines, versioning datasets, and tracking changes in model configurations and dependencies.

Ensure the security and compliance of deployed models and associated data. Implement best practices for data privacy, access control, and regulatory compliance.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or related field.

• Strong programming skills in languages such as Python.

• Experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn).

• Proficiency in cloud platforms such as AWS, Azure and related services (e.g., AWS SageMaker, Azure ML).

• Knowledge of containerization and orchestration technologies (e.g., Docker, Kubernetes).

• Familiarity with DevOps practices and tools (e.g., Git, Jenkins, Terraform).

• Experience with monitoring and logging tools (e.g., Prometheus, Grafana, ELK stack).

• Familiarity with software engineering principles and best practices (e.g., version control, testing, debugging).

• Strong problem-solving skills and attention to detail.

• Excellent communication and collaboration skills.

• Ability to work effectively in a fast-paced and dynamic environment.

Preferred Qualifications:

• Experience with big data technologies (e.g., Hadoop, Spark).

• Knowledge of microservices architecture and distributed systems.

• Certification in relevant technologies or methodologies (e.g., AWS Certified Machine Learning Specialty, Kubernetes Certified Administrator).

• Experience with data engineering and ETL processes.

• Understanding of machine learning concepts and algorithms.

• Understanding of Large Language Models (LLM) and Foundation Models (FM).

• Certification in machine learning or related fields.

Our total rewards are designed to unlock your ambition by giving you the boost and flexibility you need to turn your ideas into world-changing realities. Our salary and benefits are everything you’d expect from an organization with global strength and scale, and you’ll be surrounded by career opportunities in a culture that fosters care, collaboration and support.