Machine Learning Engineer

Job description Required Skills & Qualifications: Python: Deep expertise in Python for scripting and automation. AWS: Strong experience with AWS services, particularly SageMaker, S3, and Lambda. Terraform: Proficiency in using Terraform for infrastructure-as-code on AWS. Docker: Extensive experience with Docker, including building, managing, and securing Docker images. Linux: Strong command-line skills in Linux, especially for Docker and system management. DevOps Experience: Azure DevOps (ADO): Significant experience in setting up and managing CI/CD pipelines in ADO. Git: Proficient in using Git for version control and collaboration. Proven experience in developing and managing both batch and real-time APIs, preferably in a Kafka-based event-driven architecture. Expertise in API development, including both batch and real-time data processing. Exposure to API documentation tools like Swagger. Strong understanding of schema design and data serialization formats such as JSON. Additional DevOps Tools: Experience with Jenkins or other CI/CD tools is a plus. Experience & Education: 4 years of experience in combination of MLOps/DevOps/Data Engineering; Bachelor's degree in Computer Science, Engineering, or a related discipline. Preferred Qualifications: Experience with large language models and productionizing ML models in a cloud environment. Exposure to near real-time inference systems and batch processing in ML. Familiarity with data drift and model drift management. Job Type: Full-time Pay: $90,000.00 - $95,000.00 per year Schedule: 8 hour shift Day shift Monday to Friday Experience: Docker: 1 year (Required) AWS: 1 year (Required) APIs: 1 year (Required) Python: 1 year (Required) Terraform: 1 year (Required) Ability to Commute: Columbus, OH 43219 (Required) Work Location: In person