| Company | Symbl.ai |
| Job title | Machine Learning Engineer – Infrastructure and Operations |
| Job location | United States |
| Type | Full Time |
As a Machine Learning Engineer specializing in Infrastructure and Operations, you will play a crucial role in optimizing and scaling our AI systems for maximum performance and reliability. We leverage a range of technologies, including but not limited to:
- Machine Learning Frameworks
- Cloud Computing Services
- DevOps Tools
- Containerization Technologies
- Distributed Systems
- Monitoring and Logging Solutions
- CI/CD Pipelines
Responsibilities:
- Architect and maintain robust and scalable machine learning infrastructure.
- Collaborate with data scientists and engineers to deploy and monitor machine learning models.
- Implement automated workflows for model training, validation, and deployment.
- Optimize and fine-tune the performance of machine learning systems.
- Ensure data security, privacy, and compliance within the machine learning infrastructure.
- Troubleshoot and resolve infrastructure-related issues.
- Contribute to the evaluation and adoption of new technologies and tools in the machine learning space.
Requirements & Skills:
- Possess a strong background in machine learning, computer science, or a related field.
- Have 5+ years of experience in building and deploying machine learning models in production environments.
- Demonstrate proficiency in cloud computing platforms such as AWS, GCP, or Azure.
- Have experience with containerization technologies like Docker and orchestration tools like Kubernetes.
- Exhibit strong problem-solving skills and the ability to troubleshoot complex technical issues.
- Possess excellent communication and collaboration skills to work effectively in a remote team environment.
