Senior Machine Learning Engineer

NEORIS is a Digital accelerator that helps companies enter the future, having 20 years of experience as Digital Partners of some of the largest companies in the world. We have more than 4,000 professionals in 11 countries, with our multicultural startup culture where we cultivate innovation, continuous learning to create high-value solutions for our clients.

We are seeking a highly skilled Machine Learning Engineer with strong experience in Supply Chain, Transportation, and Delivery Analytics to support the design and development of predictive transportation delivery models. This role will focus on translating complex operational processes into scalable machine learning solutions that improve delivery efficiency, forecasting accuracy, and business decision-making.
The ideal candidate combines deep Data Science expertise with practical ML Engineering capabilities, including model experimentation, feature engineering, and production deployment using Google Vertex AI.

🔹 Machine Learning Model Development

• →Design, train, test, and optimize machine learning models focused on transportation and delivery use cases.
• →Develop predictive models primarily using XGBoost and related ML techniques.
• →Perform feature engineering, feature selection, and experiment design to improve model performance and business outcomes.
• →Evaluate model accuracy, robustness, and operational impact using appropriate statistical and ML metrics.

🔹 Supply Chain & Transportation Analytics

• →Analyze transportation and logistics workflows to identify optimization opportunities.
• →Collaborate with business stakeholders to understand operational processes, delivery constraints, and performance drivers.
• →Translate business requirements into scalable data science and ML solutions.

🔹 Data Exploration & Engineering

• →Conduct exploratory data analysis (EDA) on large operational and logistics datasets.
• →Partner with data engineering teams to ensure reliable data ingestion, transformation, and feature availability.
• →Ensure data quality, consistency, and readiness for model development.

🔹 ML Engineering & Deployment

• →Deploy and operationalize ML models using Google Vertex AI.
• →Support the implementation of scalable ML pipelines and MLOps best practices.
• →Collaborate with engineering teams to integrate models into production systems and business workflows.

🔹 Collaboration & Leadership

• →Work closely with cross-functional teams including Supply Chain, Operations, Data Engineering, and Product teams.
• →Provide technical guidance on model design, experimentation, and deployment strategies.
• →Document methodologies, findings, and implementation approaches clearly for both technical and business audiences.

• 7+ years of experience in Machine Learning, Data Science, or Advanced Analytics roles.
• Strong hands-on experience building predictive models using XGBoost or similar gradient boosting frameworks.
• Experience in Supply Chain, Transportation, Logistics, or Delivery Analytics.
• Strong expertise in:
  o Data exploration and feature engineering
  o Experiment design and model evaluation
  o Statistical analysis and predictive modeling
• Proficiency in Python and SQL for ML development and data analysis.
• Experience deploying ML solutions using Google Vertex AI or similar cloud ML platforms.
• Strong understanding of the end-to-end ML lifecycle and MLOps concepts.
• Ability to communicate effectively with both technical and business stakeholders.
• Familiarity with cloud platforms such as GCP, AWS, or Azure.
• English – Advanced (required).