Note: The job is a remote job and is open to candidates in USA. Digital Waffle is building an AI agent designed to handle genuine everyday tasks, workflows, and long-context conversations. The Senior Machine Learning Engineer will own the full ML lifecycle, from data and model training through evaluation, inference, and production deployment, while collaborating with application engineers to integrate ML across products.
Responsibilities
- Building end-to-end pipelines across data, training, evaluation, and inference
- Adapting and fine-tuning models with modern techniques: LoRA, QLoRA, SFT, DPO, distillation
- Architecting inference systems that hold up under real latency and cost constraints
- Creating data pipelines that produce high-quality synthetic and real-world training data
- Running evaluation that goes beyond benchmarks: robustness, safety, bias, production behaviour
- Owning deployment: GPU optimisation, quantisation, memory efficiency, scaling
- Working directly with application engineers so ML integrates cleanly into backend, mobile, and desktop
Skills
- Previous experience in an S-tier tech company or unicorn start-up (or equivalent)
- Deep understanding of deep learning and transformer architectures
- Proven experience training, fine-tuning, or shipping large-scale models in production
- Strong with at least one major ML framework (PyTorch, JAX) and quick to pick up others
- Familiar with distributed training and inference tooling: DeepSpeed, FSDP, Megatron, ZeRO, Ray
- Engineering discipline: code that's readable, robust, and maintainable
- Experience optimising for GPU constraints: quantisation, mixed precision, memory
- Comfortable taking ownership of ambiguous problems from zero to one
- Ships, iterates, learns from production
- LLM inference frameworks: vLLM, TensorRT-LLM, FasterTransformer
- RLHF: PPO, DPO, 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: Arrow, Spark, Ray
Benefits
- Remote work in the US
- Work closely with research and engineering leadership
- Real influence over how the architecture evolves
- See the direct impact of your work on users
Company Overview