Advance state-of-the-art AI systems by enhancing the performance and reliability of AI models through an AI Training Project.
Requirements
- Expertise in Python, with advanced knowledge of PyTorch and/or TensorFlow frameworks.
- Strong grasp of machine learning, deep learning, and model optimization techniques.
- Experience with large-scale AI training projects or AI model evaluation pipelines.
- Contributions to academic publications or open-source AI/ML communities.
- Familiarity with AI ethics, bias mitigation, or explainability in machine learning models.
Responsibilities
- Design, implement, and refine machine learning and deep learning models to support advanced AI training objectives.
- Analyze complex datasets to extract meaningful insights, ensuring robust data preprocessing and feature engineering.
- Fine-tune, optimize, and evaluate AI models to improve accuracy, efficiency, and scalability within the training pipeline.
- Develop and execute rigorous testing protocols to validate model improvements and ensure reliable deployment.
- Document experimental methodologies, results, and recommendations to support ongoing learning and process improvement.
- Stay abreast of the latest advancements in AI/ML research, integrating relevant discoveries into project work.
Other
- PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
- Proven experience conducting applied AI research and deploying machine learning solutions in real-world projects.
- Exceptional written and verbal communication skills, with the ability to simplify complex concepts for diverse stakeholders.
- Demonstrated ability to work independently and collaboratively in a remote, fast-paced team environment.
- Solid analytical, problem-solving, and organizational skills.
