About Kaleris and the Role

Kaleris builds mission-critical logistics and supply chain software used by leading operators worldwide. Join our AIML team to kickstart your engineering career working on real-world AI systems that optimize yard operations, terminal throughput, routing, and decision intelligence. You’ll learn modern ML/MLOps practices and contribute to production-grade solutions in a collaborative, inclusive environment.

What You’ll Do

• Develop, test, and deploy machine learning models for core product features (classification, regression, NLP, RL).
• Build and maintain data pipelines for ingestion, cleaning, feature engineering, and labeling.
• Implement reproducible experiments and help automate training/evaluation workflows.
• Contribute to CI/CD for ML services using containers and cloud environments.
• Monitor model performance, latency, and drift; assist in troubleshooting and incident response.
• Participate in code/design reviews; write clear documentation and visualizations for stakeholders.

Minimum Qualifications

• Bachelor’s in Computer Science, Engineering, Statistics, Mathematics, or related field.
• 0–2 years of relevant experience (internships, projects, or research count).
• Proficiency in Python and core ML/data libraries: scikit-learn, pandas, numpy.
• Familiarity with building and evaluating machine learning models and metrics.
• Knowledge of Git, unit testing, and basic software engineering practices; SQL experience.

Preferred Qualifications

• Exposure to PyTorch or TensorFlow; experiment tracking (MLflow or similar).
• Experience with Docker, Kubernetes, and a major cloud (Azure/AWS/GCP).
• Interest in logistics/supply chain and reinforcement learning concepts.

Why Kaleris

• Build AI that measurably improves global operations.
• Mentorship, growth paths, and diverse project exposure across the AIML team.
• Competitive pay, comprehensive benefits, and inclusive culture.