Machine Learning Engineer
3 weeks ago
Job Description:
As a Machine Learning Engineer specializing in infrastructure at Restored Cloud, you will design and build the tools, frameworks, and systems that enable efficient training, deployment, and scaling of machine learning models. You will work on cutting-edge challenges in model optimization, infrastructure automation, and distributed computing to support high-performance AI/ML workflows. Your work will directly impact how engineers train and deploy large-scale models seamlessly and reliably.
Responsibilities:
- Develop and maintain ML infrastructure for distributed model training and inference.
- Implement tools for model versioning, experiment tracking, and automated deployments.
- Optimize ML pipelines to improve training and inference efficiency at scale.
- Collaborate with data scientists and engineers to integrate ML workflows with existing systems.
- Monitor and ensure the reliability, security, and performance of the ML infrastructure.
- Ability to adapt to new technologies and take on new responsibilities and roles in a fast-paced growing company.
Qualifications:
- Experience with ML frameworks like TensorFlow, PyTorch, or JAX.
- Knowledge of MLOps tools such as MLflow, Kubeflow, or Airflow.
- Proficiency in containerization and orchestration tools (e.g., Docker, Kubernetes).
- Strong programming skills in Python and familiarity with CI/CD pipelines.
- Understanding of distributed training methods and hardware acceleration (e.g., GPUs, TPUs).
- Worked with LLMs and models over 10B parameters.
- 5+ years of experience in Machine Learning, Systems Engineering, or a related field.
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