R3AL.AI

About the Company

R3AL.AI develops plug-and-play AI layers that make models more efficient, reliable, and sustainable. Our Python package integrates seamlessly with PyTorch and TensorFlow to deliver built-in uncertainty quantification, out-of-distribution detection, and compute-saving optimizations. We empower enterprises to build greener, high-performance AI systems with enhanced trust and efficiency.

Listed Jobs

Company Name

R3AL.AI

Job Title

Founding ML Engineer (Optimization)

Job Description

**Job title** Founding Machine Learning Engineer (Optimization) **Role Summary** Lead the design, development, and deployment of AI optimization engines that deliver faster, cheaper, and more reliable machine‑learning models. Own the tech roadmap from MVP to scalable production, integrating directly with PyTorch and TensorFlow pipelines. **Expectations** - Work closely with the founder to set product vision and technical strategy. - Own all aspects of code quality, performance, and reproducibility. - Rapidly prototype, validate, and iterate on optimization techniques. - Champion engineering standards, documentation, and best practices from day one. - Engage with cross‑functional stakeholders (product, sales, ops) to align on value propositions. **Key Responsibilities** - Develop and refine ML algorithms for compute‑efficient inference (model pruning, quantization, distillation). - Implement uncertainty quantification and out‑of‑distribution detection modules. - Design plug‑and‑play libraries that integrate seamlessly with existing frameworks. - Conduct rigorous performance benchmarking and profiling. - Translate research concepts into production‑ready features. - Lead technical discussions, code reviews, and mentorship for junior contributors. - Shape and evolve the engineering culture and technical standards. - Monitor operational metrics and drive continuous improvement. **Required Skills** - Strong machine‑learning fundamentals (deep learning, pattern recognition, neural nets). - Proficiency in Python and experience with PyTorch/TensorFlow. - Hands‑on experience with model optimization techniques (pruning, quantization, distillation). - Knowledge of uncertainty modeling, out‑of‑distribution detection, or related safety measures. - Deep understanding of algorithms, data structures, and statistical reasoning. - Ability to prototype quickly, test rigorously, and iterate on results. - Entrepreneurial mindset with ownership of both code and product decisions. - Excellent communication skills; able to explain complex concepts to non‑technical stakeholders. **Required Education & Certifications** - Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Applied Mathematics, or a related field. - Advanced coursework or thesis in machine learning, optimization, or large‑scale AI systems preferred. - No mandatory certifications required, but experience with cloud‑based ML platforms (AWS SageMaker, GCP Vertex AI, Azure ML) is advantageous.

Ghent, Belgium

Hybrid

18-03-2026