Key Responsibilities
- Collaborate with cross-functional teams such as data scientists, software engineers, and product managers to define machine learning problems and objectives
- Research, design, and implement machine learning algorithms and models, including supervised, unsupervised, deep learning, and reinforcement learning techniques
- Analyze and preprocess large-scale datasets for training and evaluation
- Train, test, and optimize ML models to ensure accuracy, scalability, and performance
- Deploy ML models in production environments using cloud platforms and MLOps best practices
- Monitor and evaluate model performance over time to maintain reliability and robustness
- Document methodologies, results, and findings to share insights with relevant stakeholders
Required Skills and Qualifications
- Proficiency in Python or similar programming languages
- Hands-on experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn
- Strong foundational knowledge in linear algebra, probability, statistics, and optimization
- Familiarity with machine learning algorithms such as decision trees, support vector machines, and neural networks
- Understanding of key ML concepts such as feature engineering, overfitting, and regularization
- Experience working with structured and unstructured data using tools like Pandas, SQL, or Spark
- Critical thinking ability and problem-solving mindset to tackle real-world ML challenges
- Strong interpersonal and communication skills for effective collaboration in diverse teams
Preferred Skills (Good to Have)
- Experience with cloud platforms including AWS, Azure, or Google Cloud Platform
- Familiarity with MLOps tools like MLflow or Kubeflow
- Understanding of distributed computing and big data technologies such as Hadoop and Apache Spark
- Exposure to Docker and Kubernetes for deployment workflows
- Prior internships, research work, or project portfolios demonstrating ML proficiency
Technical Skills
Python, TensorFlow, PyTorch, Scikit-learn, Pandas, SQL, Spark, MLflow, Kubeflow, AWS, Azure, GCP, Hadoop, Docker, Kubernetes
Equal Opportunity Employer
DP World is an Equal Employment Opportunity (EEO) employer. We believe in building a diverse workforce and make hiring decisions based on skills and experience without regard to age, gender, disability, race, religion, or belief.