Nice to Have:

• Experience with LLM fine-tuning, Retrieval-Augmented Generation (RAG), and enterprise Generative AI applications.

• Expertise in Federated Learning, Self-Supervised Learning, and Edge AI for industrial applications.

• Background in highly regulated industries, such as finance, healthcare, or energy.

• Open-source contributions, research publications, or patents in ML engineering, AI infrastructure, or deep learning.

• Certifications such as Google Professional Machine Learning Engineer, AWS Machine Learning Specialty, or Microsoft Certified: Azure AI Engineer Expert.

What We Offer:



• Opportunity to lead and shape mission-critical AI/ML architectures for global clients.

• High-impact technical challenges with full autonomy to define and drive AI/ML innovation.

• A collaborative environment that fosters technical excellence, innovation, and continuous learning.

• Competitive salary and executive-level benefits package.

If you’re a seasoned ML Engineer with deep expertise in AI infrastructure, MLOps, and scalable machine learning systems, join Radix and lead the future of AI innovation!