Online Commerce Group, LLC - Data Scientist - Generative AI
Data Scientist is needed in Montgomery, United States.
Client: Online Commerce Group, LLC
Location: Montgomery, United States
Contract: Contractor, Part Time
Job Description
As a Data Scientist specializing in Generative AI, you will play a crucial role in developing and implementing cutting-edge generative models to solve complex problems and drive innovation. You will collaborate with cross-functional teams of data scientists, machine learning engineers, and domain experts to create novel solutions with real-world impact.
Job Duties
- Research, design, and implement generative models for various applications, such as image synthesis, text generation, and data augmentation
- Collaborate with domain experts to understand business needs and translate them into data-driven solutions using generative AI techniques
- Train and fine-tune existing generative models to improve their performance and adapt them to specific tasks
- Stay up-to-date with the latest advancements in generative AI and contribute to the company’s knowledge base by sharing insights and best practices
- Collaborate with engineering teams to deploy and integrate generative AI models into production systems
- Analyze and interpret model outputs, troubleshoot issues, and iterate on model designs to achieve desired outcomes
Job Requirements
- Bachelor’s degree in Computer Science, Data Science, Machine Learning, or a related field
- Experience working with generative AI techniques, including but not limited to GANs, VAEs, and other deep generative models
- Programming skills in languages such as Python and experience with deep learning frameworks like TensorFlow or PyTorch
- Understanding of machine learning fundamentals and statistical methods
- Experience with large-scale data processing and cloud platforms (AWS) is a plus
- Problem-solving abilities and a creative mindset to develop innovative solutions using generative AI
- Excellent communication skills to collaborate with cross-functional teams and present complex findings to both technical and non-technical stakeholders
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