Job Description:
We are looking for a Machine Learning Engineer who excels at building the infrastructure that powers intelligent features. You will be responsible for the entire lifecycle of ML models, from data ingestion and training to deployment and real-time monitoring in a cloud environment.
Your work will focus on creating robust, scalable, and efficient pipelines that ensure our AI products are reliable and lightning-fast. You will work closely with research scientists to turn experimental models into stable production services.
In this remote role, you will tackle challenges related to model latency, data drift, and distributed computing. We seek an engineer who loves clean code as much as they love high-performing models.
Responsibilities:
Build and maintain automated ML pipelines (MLOps).
Optimize model inference for production environments.
Monitor system performance and troubleshoot model degradations.
Implement data validation and quality control processes.
Preferred Qualifications:
Strong proficiency in Python and C++.
Experience with Kubernetes, Docker, and cloud platforms (AWS/GCP).
Familiarity with CI/CD for machine learning.
Solid understanding of software design patterns and system architecture.
