Senior AI Engineer

About the role

Wakapi is looking for a Senior AI Engineer to design, build, and deploy end‑to‑end machine‑learning and AI solutions that turn complex business challenges into data‑driven products. You will work closely with clients and internal teams, translating requirements into robust technical implementations.

Key responsibilities

• Perform exploratory data analysis and data wrangling on raw, messy datasets to extract actionable insights.
• Design, build, train, and evaluate machine‑learning models including regression, classification, clustering, and ensemble approaches.
• Develop predictive‑analytics solutions using Linear/Logistic Regression, Random Forests, XGBoost, and other traditional techniques.
• Integrate modern AI capabilities such as NLP, generative AI, and advanced predictive analytics into existing products.
• Manage end‑to‑end ML workflows: data preparation, feature engineering, model validation, and deployment support.
• Perform basic data‑engineering and cleaning tasks in evolving infrastructure environments.
• Collaborate with clients and stakeholders, defend technical decisions with data‑backed arguments, and adapt quickly to shifting priorities.

Required profile

• Bachelor’s degree in Computer Science, Software Engineering, or a related field.
• 5+ years of professional experience in data science, machine learning, or AI engineering.
• Strong foundation in data analysis, data wrangling, and deriving business insights using Python, Pandas, and SQL.
• Proven track record building and evaluating traditional ML models from scratch.
• Experience bridging traditional data science with modern AI applications (NLP, generative AI, predictive analytics).
• Hands‑on experience delivering end‑to‑end ML solutions in production or client‑facing settings.
• Comfort working with “dirty” data and limited infrastructure.
• Background in consulting, freelance, or startup environments with evolving roadmaps.

Required skills

• Python
• Pandas
• SQL
• Linear Regression
• Logistic Regression
• Random Forest
• XGBoost
• Classification techniques
• Clustering techniques
• Natural Language Processing (NLP)
• Generative AI
• Predictive Analytics
• Basic Data Engineering