We are partnering with a leading US-based data consultancy to find a talented MLOps Data Engineering Consultant to join their remote-first team. This is a full-time, fully remote role open to candidates located in Latin America, supporting a range of client engagements focused on deploying machine learning models into production.
About the Role:
Our client is looking for a consultant who excels at operationalizing ML workflows and building scalable data infrastructure. While prior experience designing and building ML models is a plus, the core focus is on deployment and engineering. You’ll work closely with data scientists and engineers to ensure robust, cloud-native ML pipelines.
Key Responsibilities:
* Deploy and maintain ML models in production environments.
* Build and optimize data workflows using Python and SQL.
* Collaborate with cross-functional teams to support scalable ML operations.
* Work primarily within AWS and Snowflake environments.
* Utilize AWS SageMaker for model deployment and lifecycle management.
* Contribute to multiple client projects across industries and tech stacks.
Required Skills:
* Strong experience with Python and SQL.
* Hands-on expertise with AWS, especially SageMaker.
* Familiarity with Snowflake as a data platform.
* Solid understanding of MLOps principles and CI/CD for ML.
* Comfortable working independently in a remote consulting environment.
Nice to Have:
* Experience designing and building ML models.
* Exposure to other cloud platforms (e.G., GCP, Azure).
* Familiarity with Docker and container orchestration.
Why This Role?
* Join a dynamic consultancy with a strong reputation in data and AI.
* Work remotely with a global team of experts.
* Engage in diverse, high-impact projects using modern tech stacks.