At Linnaea, we are deploying our flagship product globally directly with the leading global data management giant. Our state-of-the-art multimodal AI products are used in real clinical workflows in the USA. We're hiring for a Senior Machine Learning Engineer to help architect, deploy, and scale these systems end-to-end.
What you'll be doing (hands-on):
- Designing and deploying multimodal LLM pipelines (text + vision + reasoning multitasking)
- Building robust data processing pipelines (ETL, feature engineering, quality checks)
- Implementing post-inference automated validation, confidence scoring, and output safety layers
- Evaluating model performance beyond static and offline metrics (drift, reliability, failure modes)
- Productionizing models (serving, monitoring, iteration)
- Working closely with product & engineering to ship regulatory-aware AI
- Optimize models for scalability, cost, speed, and accuracy, and balance opposing factors
- Design and execute rigorous model validation, A/B testing, and performance benchmarking
- Monitor model drift and implement continuous learning techniques to maintain high accuracy
- Cooperate with leading tech giants tech teams, who are our partners and on whose platform our products will be integrated and launched
- Optimizing the models through devising a dynamic and innovative approach to the static loss function.
- Adapt the pipelines to comply with the USA and Europe healthcare data privacy and sovereignty
Preferred Qualifications:
- 4+ years of experience as a machine learning engineer
- Bachelor of Computer Science, Engineering, or a related discipline
- Experience in medical informatics, FHIR, HL7, and healthcare data standards is a plus
- Knowledge of adversarial attacks on ML models and AI security best practices.
- Experience and knowledge with graph neural networks (GNNs), multimodal AI, and federated
- learning, and integrating external and internal data sets
- Contributions to AI research or published work in top AI conferences (NeurIPS, ICML, CVPR, ACL, etc.)
- Experience in post-inference automation validation pipelines
Technical stack (flexible, not rigid):
- Python, PyTorch / TensorFlow
- LLM frameworks & APIs
- Data pipelines including post-inference & orchestration
- Model serving & evaluation
- Experience with healthcare data is a plus
What we're looking for:
- Strong ML fundamentals + real development and production experience
- Proven experience deploying LLMs or multimodal models
- Comfortable owning systems from data inference validation production
- Demonstrated ability to process and work smartly with datasets to ensure model accuracy
- Experience in mitigating interdependency risk
- Startup mindset: pragmatic, impact-driven, not research-only
Location: Onsite Maadi, Cairo
Why this role:
- Ownership
- Global deployment at scale
- Global real impact in healthcare AI
Perks:
- Travel to US and Europe
- Package alignment with product success
- Scalable financial windfall
- Publish research and white papers
- Competitions and conferences
- Medical insurance and exponential learning and exposure to cutting edge machine learning and reinforcement learning
- Off-sites to fun places
- Well-being packages (Therapy, Gym, and nutrition plans)
A thorough technical assessment will be conducted knowledge, hands-on experience and code
