Software Engineer
2 months ago
Responsibilities:
- Generative AI Development: Develop and implement generative models using Python and machine learning libraries like TensorFlow or PyTorch. Experiment with and apply generative AI techniques such as GANs (Generative Adversarial Networks), VAEs (Variational Autoencoders), or transformers to produce new data or content.- AI Model Integration: Integrate AI models into existing applications to enhance functionality and user experience. Work with the data science team to leverage generative models for data augmentation, synthetic data generation, and other innovative uses.- Data Management: Build robust data pipelines for training and evaluating generative AI models. Ensure data quality and process data in a way that complies with privacy and ethical standards.- Code Quality and Maintenance: Write well-designed, testable, and efficient code. Participate in code reviews and contribute to team knowledge sharing.- Research and Development: Keep up-to-date with the latest developments in generative AI and machine learning. Participate in research projects and apply findings to real-world applications.- Collaboration: Collaborate with other team members and stakeholders to meet the company's technological and strategic goals. Communicate effectively with non-technical team members to ensure alignment and understanding of AI capabilities and limitations.
Requirements:
You are:
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or a related field.- At least 8 years of professional experience in Python development.- Some experience with generative AI and familiarity with the associated machine learning techniques.- Proficient in using AI and machine learning libraries such as TensorFlow, PyTorch, or equivalent.- Strong understanding of the software development lifecycle and best practices.- Solid foundation in algorithms, data structures, and OOP concepts.- Ability to document requirements and specifications.
It would be great if you also had:
- Experience with NLP or computer vision projects.- Practical knowledge of deploying AI models in production environments.- Familiarity with cloud services and APIs.- Experience with version control systems, preferably Git.
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