AI Engineer

About this role

We're building a sovereign AI platform that puts control back in the hands of users. You'll work on the full AI stack—from model fine-tuning and RAG pipelines to inference optimization and deployment at scale. You should be comfortable navigating ambiguity, prototyping fast, and iterating based on real-world feedback. We care less about credentials and more about what you've built. Ideal if you've shipped ML systems in production, have opinions about LLM architectures, and get excited about making AI accessible and private.

What You'll Do

Design and implement ML pipelines for training, evaluation, and deployment

Optimize model inference for cloud, edge, and on-premise environments

Develop and maintain model serving infrastructure

Build RAG pipelines and LLM-based applications

Implement techniques for privacy-preserving ML

Create tools for automated model monitoring and retraining

What You Bring

3+ years of experience in machine learning engineering

Strong Python skills and experience with ML frameworks (PyTorch, TensorFlow)

Experience with MLOps—model versioning, experiment tracking, deployment

Understanding of LLMs, RAG, and modern NLP techniques

Familiarity with Docker, Kubernetes, and cloud infrastructure

Bonus Points

Experience with edge deployment (ONNX, TensorRT, Core ML)

Background in computer vision or structured data ML

Contributions to open-source ML projects

Experience with privacy-preserving ML techniques