
Foodics
Senior Data Scientist / Senior ML Engineer
- Permanent
- Riyadh, Saudi Arabia
- Experience 5 - 10 yrs
- Urgent
Job expiry date: 30/10/2026
Job overview
Date posted
15/09/2026
Location
Riyadh, Saudi Arabia
Salary
SAR 30,000 - 40,000 per month
Compensation
Comprehensive package
Experience
5 - 10 yrs
Seniority
Senior & Lead
Qualification
Bachelors degree
Expiration date
30/10/2026
Job description
Foodics has processed over 6 billion orders through its restaurant management and payment technology platform, and this role owns the ML, AI and GenAI models sitting behind products like pricing, personalization and fraud detection. You lead the full model lifecycle, from problem framing and data exploration through training, deployment and ongoing monitoring. Classical ML and GenAI techniques both come into play, built into solutions designed to scale across the platform. MLOps practices run throughout the work, covering versioning, reproducibility and CI/CD so models stay maintainable long after launch. Data Engineers, Product Managers and Platform teams all collaborate closely with this role, keeping models reusable and aligned with internal standards. A "you build it, you run it" mindset shapes how ownership works here, with full responsibility for a model from development through continuous improvement. Junior ML engineers get mentored along the way, and contributions to the internal ML knowledge base help the wider team level up. APIs and backend services get integrated with these models as needed, connecting the ML work directly to what customers actually experience.
Required skills
Key responsibilities
- Own the end-to-end ML model lifecycle from problem framing through monitoring
- Design and develop scalable solutions using classical ML and GenAI techniques
- Implement MLOps best practices including versioning and CI/CD for models
- Collaborate with squads and platform teams to ensure reusability and standards adherence
- Mentor junior ML engineers and contribute to the internal ML knowledge base
- Integrate models with APIs and backend services as needed
- Enforce a "you build it, you run it" approach across the model lifecycle
Experience & skills
- Bring 5+ years of experience in applied ML, AI or data science
- Demonstrate strong proficiency in Python and ML/AI libraries such as PyTorch and TensorFlow
- Apply MLOps tools such as MLflow or SageMaker for versioning, testing and observability
- Show deep understanding of model development workflows including feature engineering and A/B testing
- Communicate statistical modeling results clearly to technical and non-technical audiences
- Carry a proven track record of deploying ML models in production at scale
- Use GenAI and LLM integration tools such as LangChain, LangGraph or LlamaIndex