Job role:We are looking for a talented Machine Learning Engineer with a focus on Artificial Intelligence to join Promptly.
The ideal candidate will have a strong background in data science, machine learning, and AI technologies.
This role requires a deep understanding of AI algorithms, natural language processing, computer vision, and the ability to apply AI techniques to solve complex business problems.Responsibilities:Ensure that data flows smoothly from source to destination so that it can be processed.Develop and implement AI models to solve business challenges.Gather, preprocess, and curate data for AI model development.Filter and cleanse unstructured (or ambiguous) data into usable data sets that can be analyzed to extract insights and improve business processes.Evaluate AI model performance using relevant metrics and optimize models for improved accuracy and efficiency.Continuously explore and implement new techniques to enhance AI capabilities.Identify new internal and external data sources to support analytics initiatives and work with appropriate partners to absorb the data into new or existing data infrastructure.Build tools for automating repetitive tasks so that bandwidth can be freed for analytics.Work closely with cross-functional teams, including software developers, data engineers, and business analysts.Requirements:Bachelor's or Master's in a quantitative field (such as Engineering, Statistics, Math, Economics, or Computer Science with Modeling/Data Science).Ability to program in any high-level language is required.
Familiarity with R and statistical methods is a plus.Proven problem-solving and debugging skills.In-depth knowledge of machine learning algorithms and AI techniques.Ability to creatively apply AI solutions to real-world business problems.Familiarity with computer vision libraries and frameworks (e.G., OpenCV, TensorFlow, PyTorch, Transformers, NLTK).Experience with text analytics, data mining, and social media analytics.Statistical knowledge in standard techniques: Logistic Regression, Classification models, Cluster Analysis, Neural Networks, Random Forests, Ensembles, etc.#J-18808-Ljbffr