The MLOps Engineer is responsible for closing the gap between machine learning models development and their operational deployment. This role ensures that machine learning models are efficiently running in the production environment and are continuously monitored for performance. The MLOps Engineer contributes to Arbitration Forums AI-powered portfolio of products and services by enhancing the scalability and reliability of machine learning applications.
Requirements
- Working knowledge of cloud services (i.e., MS Azure, AWS, Google Cloud).
- Experience with AI tools, such as MS Azure ML, Snowflake, Databricks, CortexAI, Dataiku.
- Deep understanding of data science principles, algorithms, and tools.
- Strong knowledge of data governance, data security, and compliance practices.
- Proficiency in programming languages such as Python, R, or Java.
- Experience with containerization tools like Docker and orchestration tools like Kubernetes.
- Proficiency in ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.
Responsibilities
- Design, implement, and maintain machine learning pipelines and workflows for the continuous deployment and integration of machine learning models. Optimize the pipelines for scalability, efficiency, and cost-effectiveness.
- Collaborate with data scientists and AI engineers to understand model requirements and optimize deployment processes.
- Automate the training, testing, and deployment processes for machine learning models.
- Establish and enforce best practices for version control, documentation, and code quality in ML projects.
- Monitor model performance and optimize algorithms for efficiency.
- Conduct regular maintenance and updates to deployed models.
- Maintain and optimize the cloud-based machine learning infrastructure and make recommendations for improvements.
Other
- Adheres to AF Policy and Procedures and the AF IPAAL Values and TRI Model
- Acts as a role model within and outside AF.
- Performs duties as workload necessitates.
- Maintains a positive and respectful attitude.
- Communicates regularly with the departmental leader about department issues.
