AI/Machine Learning Engineer

The Role:

We're searching for a talented Machine Learning Engineer with a passion for Artificial Intelligence to join our team at Promptly! This is a full-time position based in either Porto or Lisbon, Portugal. If you have a strong background in data science, machine learning, and AI technologies, and enjoy applying AI techniques to solve complex business problems, we want to hear from you.

What You'll Do:

• Ensure smooth data flow from source to destination for processing.
• Develop and implement AI models to tackle business challenges.
• Gather, preprocess, and curate data for AI model development.
• Transform unstructured or ambiguous data into usable datasets for analysis and business process improvement.
• Evaluate AI model performance using relevant metrics and optimize for accuracy and efficiency.
• Continuously explore and implement new techniques to enhance AI capabilities.
• Identify new internal and external data sources for analytics initiatives and collaborate with partners to integrate data into existing infrastructure.
• Build tools to automate repetitive tasks, freeing up time for analytics.
• Collaborate closely with cross-functional teams (software developers, data engineers, business analysts).

What You'll Need:

• Education: Bachelor's or Master's degree in a quantitative field (Engineering, Statistics, Math, Economics, or Computer Science with a focus on Modeling/Data Science).
• Programming Skills: Proficiency in at least one high-level programming language is required. Familiarity with R and statistical packages is a plus.
• Problem-Solving: Proven problem-solving and debugging skills.
• AI Expertise: In-depth knowledge of machine learning algorithms and AI techniques.
• Creative Application: Ability to creatively apply AI solutions to real-world business problems.
• Technical Skills: Familiarity with computer vision libraries and frameworks (e.g., OpenCV, TensorFlow, PyTorch, Transformers, NLTK).
• Data Analysis: Experience with text analytics, data mining, and social media analytics.
• Statistical Knowledge: Understanding of standard statistical techniques: Logistic Regression, Classification models, Cluster Analysis, Neural Networks, Random Forests, Ensembles, etc.