Note: The job is a remote job and is open to candidates in USA. Digital Waffle is focused on building genuine AI products that assist users with various tasks. They are seeking a Senior Machine Learning Engineer to own the ML layer, bridging research and production while developing end-to-end systems that are reliable and scalable.
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
- 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
Company Overview