Senior Machine Learning Engineer in Edinburgh

Senior Machine Learning Engineer (AI Training)What if your deep expertise in machine learning could directly shape how the next generation of AI systems reason, plan, and solve complex problems?We're looking for Senior Machine Learning Engineers to work on one of the most technically challenging and impactful problems in AI today: teaching large language models how to think. You'll author high-fidelity reasoning traces — structured, step-by-step records of how an LLM should plan, use tools, and arrive at decisions — creating the training data that makes AI more reliable and capable in real-world scenarios. This is a fully remote, flexible contract role built for senior-level engineers who want to work at the frontier of AI development without the constraints of a full-time position.Organization: AlignerrType: Hourly ContractLocation: RemoteCommitment: 10–40 hours/weekWhat You'll DoAuthor complex, high-fidelity reasoning traces that document how LLMs should approach sophisticated technical tasks — including planning, tool use, and multi-step decision makingDesign and implement data strategies that help AI models navigate intricate, real-world scenarios with greater reliabilityReview and evaluate reasoning traces for logical consistency, structural quality, and completenessDecompose advanced ML problems into clear, well-documented reasoning steps that serve as model training examplesApply your knowledge of LLM architectures and training methodologies to ensure traces meet rigorous quality standardsWho You AreExperienced machine learning engineer or researcher with deep knowledge of model reasoning, architecture, and trainingSkilled at breaking down complex technical problems into logical, clearly documented stepsFamiliar with advanced LLM evaluation techniques and how model behavior is shaped by training dataDetail-oriented and systematic — you hold yourself to high standards of precision and claritySelf-directed and comfortable working asynchronously in a remote environmentNice to HavePrior experience with data annotation, data quality assurance, or AI evaluation systemsTop-tier Kaggle competition results (Grandmaster or Master level) demonstrating advanced model performance and feature engineering expertiseHands-on experience with RLHF, chain-of-thought prompting, or other reasoning-focused training methodologiesBackground in AI safety, interpretability, or alignment researchWhy Join UsWork directly with world-leading AI research teams on problems that matterFully remote and flexible — work when and where it suits you, on your own scheduleFreelance autonomy with the substance of meaningful, high-impact technical workGain rare, hands-on exposure to how frontier LLMs are trained and evaluatedContribute to advancing AI systems that are more reliable, transparent, and capable in the real worldPotential for ongoing work and contract extension as new projects launch
#J-18808-Ljbffr