About Webb Fontaine

Founded in 2002, Webb Fontaine is a global trade technology company headquartered in Dubai, with projects spanning the Middle East, Africa, Asia, South America and beyond. We partner with governments worldwide, providing cutting-edge solutions to boost their revenue by streamlining trade and logistics operations across the entire trade spectrum.

At Webb Fontaine, we're crafting a legacy of innovation with a mission to transform the landscape of trade through technology. This wouldn’t be possible without our team of exceptional individuals who are at the core of our success.

Position Summary

We are seeking a results-driven Machine Learning Engineer to join our team. In this role, you will be responsible for managing the end-to-end lifecycle of machine learning models, including deployment, monitoring, and optimization in production. You will work closely with ML engineers and the infrastructure team to ensure scalable, reliable, and efficient machine learning systems.

Key Responsibilities

• Collaborate with ML specialists to productize and deploy machine learning models into production environments.
• Collaborate with DevOps and data engineering teams to integrate machine learning models with other system components.
• Establish and manage automated pipelines for continuous integration and continuous deployment (CI/CD) of ML models.
• Monitor and track model performance in production, ensuring that models meet expected accuracy and performance benchmarks.
• Continuously retrain, fine-tune, and update models based on new data and performance metrics.
• Implement and monitor data versioning, quality checks, and consistency measures to ensure reliable model inputs.
• Lead efforts to improve and optimize model inference speed, resource usage, and scalability in production environments.
• Deploy and manage self-hosted Large Language Models (LLMs) in production environments, ensuring optimal performance and scalability.

Qualifications

• Proven experience as a Machine Learning Engineer with expertise in model deployment and operations.
• Proficiency in Python and ML libraries such as scikit-learn, NumPy, pandas, and familiarity with model serving platforms such as Flask, FastAPI
• Strong experience in ML Ops tools and techniques, including CI/CD pipelines, model versioning, and monitoring.
• Hands-on experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies like Docker and Kubernetes.
• Experience in deploying and managing self-hosted LLMs is a plus.
• Strong knowledge of model monitoring tools (e.g., Prometheus, Grafana) and logging systems for error tracking.
• Excellent knowledge of English for effective communication and documentation.

Benefits

• Equal opportunity advocacy: We promote equality, creating a diverse and inclusive environment.
• Competitive compensation: Enjoy a competitive salary that rewards your contributions.
• Health and Wellness: We provide comprehensive medical coverage.
• Global collaboration: Join a world-class team with a global presence and international clients.
• Investment in you: We invest in your growth and development, valuing our employees as top talent.
• Work-life balance: We ensure a healthy work-life balance for your well-being.
• Training support: We offer a comprehensive learning and development program.
• Personalised approach: We prioritise personal connections, and caring for you beyond your professional role.

We offer benefits tailored to each location, considering the specific regulations and conditions of each country. These will be discussed with candidates during the selection process.