المسؤوليات والمهام الأساسية
AI is useful when it reduces real work—not when it becomes a demo that never reaches users.
ErthDev is looking for an AI / ML Engineer to help integrate practical machine-learning and AI capabilities into client products and internal tools.
You'll focus on applied systems: reliable pipelines, evaluation, and product-ready integrations.
What you'll do
- Prototype and implement AI/ML features for products.
- Evaluate models, prompts, and approaches against clear success criteria.
- Build data preparation and inference pipelines.
- Integrate AI services into backend and product workflows.
- Measure quality, cost, latency, and failure modes.
- Collaborate with product, backend, and security teams on responsible usage.
- Document assumptions, evaluation results, and operational constraints.
- Improve monitoring for AI-powered features.
- Help teams decide when AI is the wrong tool.
- Protect client data and confidentiality in AI workflows.
AI at ErthDev
We treat AI as a product capability with risk, cost, and quality constraints.
We care about evaluation, privacy, and operability—not hype cycles.
What you'll get
- Fully remote work from Egypt
- Flexible working hours with collaboration overlap
- Cairo office access when needed
- Paid annual leave and sick leave
- Performance bonuses and annual salary reviews
- Learning and development support
- Courses and certifications
- Conference opportunities
- Equipment and internet support
- Medical insurance
- Mentorship and career growth
- Exposure to projects across different industries
Hiring process
Application → Initial Conversation → Practical Assessment → Technical Interview → Final Conversation → Offer
If you can separate useful AI from impressive demos, we'd like to talk.
Apply through LinkedIn Easy Apply or the ErthDev careers page.
المعايير والخبرات المطلوبة
What we're looking for
- Practical experience shipping AI/ML features or prototypes into production-adjacent systems.
- Strong Python skills.
- Understanding of model evaluation and failure analysis.
- Familiarity with LLMs and/or classical ML workflows.
- Ability to work with APIs, data pipelines, and backend engineers.
- Clear communication of uncertainty and trade-offs.
- Security and privacy awareness.
- Product-minded problem solving.
Experience with PyTorch, scikit-learn, vector search, LangChain/LlamaIndex (or equivalent), cloud ML services, and evaluation frameworks is a plus.