Senior Data Scientist / Senior Machine Learning Engineer

About Foodics

Foodics is a prominent restaurant management and payment technology platform, established in 2014 and based in Riyadh with offices across the UAE, Egypt, Jordan, and Kuwait. Serving clients in over 35 countries, Foodics has processed upwards of 6 billion orders and is recognized as one of the fastest growing SaaS firms in the MENA region. Recently, it secured $170 million in funding, the largest SaaS investment round in the region, to further enhance its innovative solutions for business owners.

Role Overview

As a Senior Data Scientist / ML Engineer, you will spearhead the end-to-end lifecycle of machine learning and AI model development to support key Foodics products such as pricing strategies, customer personalization, and fraud prevention systems. This role involves extensive collaboration with data engineering, product, and platform teams to deliver robust, production-ready models that make a tangible business impact.

Key Responsibilities

• Lead the full ML model lifecycle: defining problems, exploring data, training models, deploying, and ongoing monitoring.
• Develop scalable algorithms using classical machine learning and generative AI methods.
• Implement MLOps practices including model versioning, ensuring reproducibility, continuous monitoring, and integrating CI/CD workflows.
• Work closely with cross-functional teams to promote code reuse and maintain compliance with coding and operational standards.
• Provide mentorship to junior ML engineers and contribute to collective machine learning knowledge resources.
• Integrate machine learning models with APIs and backend systems where required.
• Adopt a "you build it, you run it" philosophy, being accountable for your models throughout their lifecycle, from creation through deployment to monitoring and refinement.

Qualifications and Experience

• A minimum of 5 years’ experience in applied machine learning, artificial intelligence, or data science roles.
• Proficient in Python programming along with extensive use of ML/AI frameworks such as scikit-learn, PyTorch, TensorFlow, XGBoost, and HuggingFace Transformers.
• Hands-on experience with MLOps tooling including MLflow and SageMaker, focusing on model version control, testing, and performance monitoring.
• In-depth knowledge of feature engineering, hyperparameter tuning, model validation techniques, and A/B testing frameworks.
• Strong grasp of statistical modeling, inference methods, and application of tests including t-test, chi-square, ANOVA, and regression; with the capability to clearly communicate results to varied audiences.
• Proven success deploying machine learning models at scale in production environments.
• Expertise in machine learning best practices encompassing bias reduction, explainability techniques like SHAP and LIME, and monitoring for drift and fairness.
• Solid understanding of data processing pipelines, experimental design, and evaluation methodologies.
• Experience working in cloud-native environments, preferably AWS, using infrastructure-as-code (Terraform, CDK) and CI/CD, GitOps approaches.
• Practical knowledge with generative AI and large language model integrations such as retrieval-augmented generation, fine-tuning, embeddings, and prompt engineering using tools like LangChain, LangGraph, or LlamaIndex.

What Foodics Offers

• A culture that embraces inclusivity and diversity, fostering innovation.
• Competitive salary packages with bonuses and potential equity participation.
• Focus on professional growth with regular training and an annual budget for learning to advance your career in a fast-growing organization.
• Opportunity to work within a multicultural team of 30+ nationalities across 14 countries, gaining valuable experience in the dynamic restaurant tech sector.
• Autonomy in your role, with mentoring and challenging objectives that provide meaningful opportunities for career advancement and company impact.