machine learning engineer for AI agents

Digital Waffle is building an AI agent that performs genuine tasks for everyday users, manages workflows, and maintains context across long and complex conversations. The company develops reliable AI products where the machine learning layer is the core product.

• Build end-to-end pipelines across data, training, evaluation, and inference;
• Adapt and fine-tune models using LoRA, QLoRA, SFT, DPO, and distillation;
• Architect inference systems under real latency and cost constraints;
• Create pipelines for high-quality synthetic and real-world training data;
• Run evaluations covering robustness, safety, bias, and production behaviour;
• Own deployment, including GPU optimisation, quantisation, memory efficiency, and scaling;
• Work directly with application engineers to integrate ML into backend, mobile, and desktop products;
• Take ownership of ambiguous problems from zero to one;
• Ship, iterate, and learn from production.

• Deep understanding of deep learning and transformer architectures;
• Proven experience training, fine-tuning, or shipping large-scale models in production;
• Strong proficiency with at least one major ML framework, such as PyTorch or JAX;
• Familiarity with distributed training and inference tooling, including DeepSpeed, FSDP, Megatron, ZeRO, or Ray;
• Engineering discipline and ability to write readable, robust, and maintainable code;
• Experience optimising for GPU constraints, including quantisation, mixed precision, and memory;
• Ability to work autonomously on ambiguous problems;
• Nice to have: LLM inference frameworks such as vLLM, TensorRT-LLM, or FasterTransformer; RLHF with PPO, DPO, or ORPO; open-source contributions to ML or systems libraries; scientific computing, compiler, or GPU kernel experience; multimodal or diffusion model background; large-scale data processing with Arrow, Spark, or Ray.

• Work location is the European Union;
• The role offers close collaboration with research and engineering leadership and direct influence over architecture evolution.