Senior ML/AI Engineer

Summary Build, train, and deploy machine learning models — with a focus on LLM fine-tuning and high-performance inference pipelines. You own models from experimentation through to reliable production serving. Role Expectations Train, fine-tune, and evaluate models — including LLMs via full fine-tuning, LoRA/PEFT, and instruction tuning. Build and optimize inference pipelines for latency, throughput, and cost (batching, quantization, caching). Design data pipelines and datasets for training and evaluation; ensure data quality and reproducibility. Implement rigorous offline and online evaluation, benchmarking, and regression testing for models. Partner with platform engineers to deploy models to production with monitoring and rollback. Stay current with model architectures and translate research into practical improvements. Required Skills 5+ years in ML/AI engineering; proven track record shipping models to production. Strong Python and deep learning with PyTorch; solid understanding of the Transformer architecture. Hands-on LLM fine-tuning experience (LoRA/PEFT, quantization, or full fine-tuning). Experience building inference/serving pipelines and measuring model performance. Comfortable with experiment tracking, versioning, and MLOps fundamentals. Value adds: Distributed training experience (multi-GPU, DeepSpeed, FSDP). Publications, competition results, or notable open-source ML work. Experience with retrieval, embeddings, and evaluation frameworks. Core Stack: Python · PyTorch · Transformers · LLM Fine-Tuning · MLOps · Prompt Engineering