Able to collaborate with data scientists to develop and fine-tune machine learning models, including but not limited to deep learning, natural language processing, computer vision, and reinforcement learning.
Able to clean, preprocess, and transform data into a format suitable for training and evaluation of machine learning models. Implement data augmentation and feature engineering techniques when necessary.
Able to train, validate, and optimize machine learning models using relevant frameworks and libraries. Tune hyperparameters and experiment with different architectures to improve model performance.
Able to deploy machine learning models into production environments, ensuring scalability, reliability, and performance. Integrate models into applications, APIs, or microservices as needed.
Able to stay up to date with the latest advancements in AI and ML technologies. Experiment with new algorithms and techniques to enhance the capabilities of our AI/ML systems.
Requirements:
You are:
Proven experience in developing and deploying machine learning models and algorithms.
Proficiency in programming languages such as Python, TensorFlow, PyTorch, or similar.
Strong knowledge of data preprocessing, feature engineering, and model evaluation techniques.
Familiarity with cloud computing platforms (e.g., AWS, Azure, GCP) for model deployment.
Excellent problem-solving skills and a passion for working on challenging AI/ML problems.
Effective communication skills and the ability to work in a collaborative team environment.
Experience with version control systems (e.g., Git) is a plus.