Federated Learning and Differential Privacy Engineer (Remote)
Remote
AI Summary
Join Socium's remote team as a Federated Learning and Differential Privacy Engineer. You will design and implement machine learning workloads using Federated Learning and Differential Privacy. The ideal candidate has experience with MLOps, Data Engineering, or DevOps, and proficiency in Python, containerization, and MLOps tools.
Key Highlights
Federated Learning and Differential Privacy
MLOps, Data Engineering, or DevOps
Python, containerization, and MLOps tools
Technical Skills Required
Benefits & Perks
Remote work
Flexible work arrangement
Job Description
- FULLY REMOTE ROLE
- Must have: Experience with Federated Learning and Differential Privacy
- Skills: MLOps, Data Engineering, or DevOps, Python, containerization (Docker, Kubernetes), and MLOps tools (e.g., MLflow, Kubeflow, Sagemaker)
- Knowledge of cloud infrastructure and services for machine learning workloads.
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