Machine Learning Engineer

Senior Machine Learning Engineer talent pool in London, focused on failure analysis rather than a single headline metric. Employer assignments use this pool when they need a Machine Learning Engineer in London, United Kingdom, who is accountable for failure analysis rather than a single headline metric. The useful week is spent slicing errors, checking label quality, and refusing a model that only wins on an average, with mistakes corrected in the open rather than buried. Responsibilities - Review the slice report for the weak segments and correct it before anyone else relies on it. - Keep a single current label audit, and archive the older copy once you have dealt with the inconsistent labels. - Ask the person who will use the prediction to challenge the threshold note, especially around a cutoff that harms one group. - Write the assumption behind the comparison table in two or three plain sentences, and mention a baseline that was never run. - Compare this week's drift check with the previous one and explain the input shift. - Stop and rework the limitation note if you find the cases the model must not decide. Requirements - Roughly 5 to 8 years of judging model quality beyond a single score that matches this machine learning engineer profile, or a shorter record with the same kind of finished work. - Practical skill with Python, evaluation metrics, and data slicing in machine learning engineer work, not a certificate alone. - Able to explain which users a threshold will treat worse to a colleague who was not in the room. - Careful with models shipped on an average score alone; this is checked in review of machine learning engineer work. - For the machine learning engineer brief in London, use the working language of that assignment in United Kingdom. Nice to have - Fairness or slice reviews is useful on machine learning engineer assignments in London, and it is not required. - People who have already done label audits can start this machine learning engineer brief with less coaching. - Clear limitation statements is a plus for machine learning engineer work based in London. Skills Python, SQL, model evaluation, feature design, experiment notes, data slicing, version control, technical writing Working conditions This is an on-site machine learning engineer listing in London, United Kingdom. Work happens at the assignment's premises. The usual week is Monday to Friday, on UK time. The work is desk-based. Training jobs may run outside the working day and need a check the next morning. Location The hiring base for this machine learning engineer listing is London, United Kingdom. English is the working language for this London brief. Qualified people are considered without regard to race, color, religion, sex, national origin, age, disability, or other characteristics protected by applicable law. This is a talent-pool listing. Your profile will be reviewed and matched to employer openings that fit; submitting an application does not guarantee an interview or placement.