- Build AI Infrastructure: Contribute to the development and maintenance of scalable, reliable, and efficient infrastructure for training and deploying machine learning models.
- MLOps & Automation: Implement and maintain CI/CD pipelines for machine learning models, helping to automate the entire lifecycle from data preparation to model monitoring.
- Production Deployment: Deploy and maintain machine learning models in our production environments, ensuring high availability, low latency, and scalability.
- Software Development: Write clean, high-quality, and production-ready code to support AI/ML initiatives.
- Cross-Functional Collaboration: Partner with data scientists, other engineers, and product managers to understand model requirements and translate them into robust engineering solutions.
- Performance Optimization: Help monitor and optimize the performance of our AI systems, including model inference speed, resource utilization, and cost-effectiveness.
- Technology & Tooling: Work with modern tools, frameworks, and technologies in our AI engineering stack and stay current with the latest advancements in the field.
- Code Quality & Best Practices: Maintain and adhere to high standards for code quality, testing, and documentation.
- Educational Background: Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related technical field.
- Professional Experience: 3+ years of professional software engineering experience, with at least 1-2 years focused on AI/ML engineering, MLOps, or a similar backend role.
- Software Engineering Excellence: Strong proficiency in a major programming language (e.g., Python, Java, Go) and a solid foundation in software architecture, data structures, and algorithms.
- MLOps Knowledge: Hands-on experience building or maintaining MLOps pipelines using tools like Kubernetes, Docker, Jenkins, MLflow, Kubeflow, or similar technologies.
- Cloud Proficiency: Experience with at least one major cloud platform (AWS, GCP, or Azure) and its core services. Familiarity with its AI/ML services is a plus.
- Problem-Solving: Strong analytical and problem-solving skills, with the ability to troubleshoot technical issues.
- Experience with large-scale data processing technologies (e.g., Apache Spark, Kafka).
- Familiarity with infrastructure as code (IaC) tools like Terraform or CloudFormation.
- Experience optimizing deep learning models for inference (e.g., using TensorRT, ONNX).
- A passion for building and shipping products with AI at their core.
Skills Required
- Bachelor's or Master's degree in Computer Science, Software Engineering, or a related technical field
- 3+ years of professional software engineering experience, with at least 1-2 years focused on AI/ML engineering, MLOps, or a similar backend role
- Strong proficiency in a major programming language (e.g., Python, Java, Go)
- Hands-on experience building or maintaining MLOps pipelines using tools like Kubernetes, Docker, Jenkins, MLflow, Kubeflow, or similar technologies
- Experience with at least one major cloud platform (AWS, GCP, or Azure) and its core services
- Strong analytical and problem-solving skills
What We Do
Our mission is to enable efficient and sustainable delivery of excellent care. The IKS Care Enablement Platform enables us to deliver the chores of healthcare, across administrative, clinical, and operational burdens, enabling clinicians and staff to focus on their core purpose of delivering great care to their patients. IKS Health creates transformative value in healthcare through a unique combination of cutting edge technology and dedicated experts that empowers clinicians to build healthier communities, and enables stronger, financially sustainable enterprises. Our global team of 14,000, including 600+ technologists and 2,600+ clinical staff, enables 150,000 clinicians to rediscover the joy of medicine. IKS Health is the trusted partner for 900+ clients including the largest hospitals, health systems, and specialty groups across the United States.
