Walmart is looking to design, build, and maintain machine learning models and pipelines, as well as ensure the smooth operation of their ML infrastructure. The ideal candidate will have experience with popular ML frameworks and languages, and be able to work with cross-functional teams to integrate ML models with large language models (LLMs) and other AI/ML technologies.
Requirements
- 3+ years of experience in ML Ops, data engineering, or a related field
- Strong programming skills in Python, Java, or C++
- Experience with ML frameworks such as TensorFlow, PyTorch, or Scikit-Learn
- Experience with LLMs and natural language processing (NLP) techniques
- Strong understanding of data pipelines, data storage, and data processing systems
- Bachelor's degree in Computer Science, Engineering, or related field
- Master’s degree in Computer Science, Computer Engineering, Computer Information Systems, Software Engineering, or related area and 1 year's experience in software engineering or related area.
Responsibilities
- Design and implement ML models and pipelines using popular frameworks such as TensorFlow, PyTorch, or Scikit-Learn
- Collaborate with data scientists to develop and deploy ML models, ensuring seamless integration with existing infrastructure
- Develop and maintain ML infrastructure, including data pipelines, data storage, and data processing systems
- Ensure the scalability and reliability of ML models and pipelines, troubleshooting issues as needed
- Work with cross-functional teams to integrate ML models with large language models (LLMs) and other AI/ML technologies
Other
- Excellent problem-solving skills and attention to detail
- Strong communication and collaboration skills
- Bachelor's degree in Computer Science, Engineering, or related field
- Option 1: Bachelor's degree in computer science, computer engineering, computer information systems, software engineering, or related area and 3 years’ experience in software engineering or related area.
- Option 2: 5 years’ experience in software engineering or related area.
