Machine Learning Specialist - stable diffusion

• Utilize your expertise in Amazon SageMaker to build, train, and deploy machine learning models, ensuring efficient and scalable implementations.
• Implement stable diffusion techniques to model physical systems and tackle real-world challenges.
• Apply your knowledge of ControlNet to develop interconnected control loops and optimize system behavior using ML techniques.
• Build and automate ML pipelines (e.g., Automatic1111) for data preprocessing, model training, and deployment, streamlining the development process.
• Demonstrate proficiency in Python programming and various machine learning algorithms to solve complex problems and deliver innovative solutions.
• Conduct thorough data preprocessing, including cleaning, transformation, and feature engineering, to ensure high-quality input for ML models.
• Evaluate and validate model performance using industry-standard techniques, and fine-tune hyperparameters to achieve optimal results.
• Leverage your understanding of deep learning architectures, such as CNNs, RNNs, and transformers, for advanced ML applications.
• Collaborate with cross-functional teams to deploy ML models into production environments, ensuring seamless integration with existing systems.
• Utilize version control systems like Git to manage codebase efficiently and promote collaborative development practices.

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• Proven experience in utilizing Amazon SageMaker for machine learning model development and deployment.
• Demonstrated expertise in stable diffusion techniques, ControlNet implementation, and building automated ML pipelines.
• Proficiency in Python programming, along with experience in popular libraries like NumPy, Pandas, Scikit-learn, TensorFlow, and PyTorch.
• Strong understanding of machine learning algorithms, data preprocessing, and model evaluation.
• Familiarity with deep learning architectures and their applications in computer vision, natural language processing, or other domains.
• Experience with cloud computing platforms like AWS, Google Cloud, or Azure is a plus.
• Knowledge of PHP for web-related ML projects and integrations is desirable but not mandatory.
• Excellent problem-solving skills, a passion for innovation, and a proactive mindset.
• Strong communication and teamwork abilities to collaborate effectively with colleagues and stakeholders.

• Work alongside & learn from best in class talent
• Excellent career development opportunities
• Salary in USD

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