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Research Scientist
IBM
Yorktown Heights, NY, USA
Posted on Tuesday, September 10, 2024
Introduction
IBM Research is seeking a highly skilled and motivated AI Scientist/Engineer with expertise in PyTorch to join our team. In this role, you will be responsible for developing, training, and deploying sophisticated machine learning models. You will collaborate with a cross-functional team to translate business requirements into robust AI solutions, ensuring high performance and scalability.
Your Role and Responsibilities
Develop, train, and optimize machine learning models using PyTorch.
Collaborate with cross-disciplinary teams to understand requirements and formulate AI-driven solutions.
Implement state-of-the-art algorithms and contribute to the development of our AI platform.
Evaluate and improve the performance of machine learning models.
Stay abreast of latest developments in AI and machine learning, especially in PyTorch.
Required Technical and Professional Expertise
IBM Research is seeking a highly skilled and motivated AI Scientist/Engineer with expertise in PyTorch to join our team. In this role, you will be responsible for developing, training, and deploying sophisticated machine learning models. You will collaborate with a cross-functional team to translate business requirements into robust AI solutions, ensuring high performance and scalability.
Your Role and Responsibilities
Develop, train, and optimize machine learning models using PyTorch.
Collaborate with cross-disciplinary teams to understand requirements and formulate AI-driven solutions.
Implement state-of-the-art algorithms and contribute to the development of our AI platform.
Evaluate and improve the performance of machine learning models.
Stay abreast of latest developments in AI and machine learning, especially in PyTorch.
Required Technical and Professional Expertise
- Contributions to open-source machine learning projects, especially PyTorch.
- Contribute to the codebase ensuring best practices in software development.
- Prepare and present findings to both technical and non-technical stakeholders.
Preferred Technical and Professional Expertise
- Experience with other deep learning frameworks (e.g., TensorFlow).
- Familiarity with cloud platforms (e.g., Kubernetes/OpenShift, AWS, GCP, Azure) and their machine learning services.
- Experience with distributed training technologies (e.g., FSDP).