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  "job_title": "Lead ML Engineer (SageMaker)",
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  "job_posted_at": "2 days ago",
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  "job_description": "Job Title: Lead Machine Learning Engineer (SageMaker, MLOps, Explainability)\nJob DescriptionWe are seeking an experienced Lead Machine Learning Engineer to design, build, and productionise machine learning models for our innovative matching platform. You will work across the entire ML lifecycle, from feature engineering to deployment automation, ensuring the optimisation and explainability of inference processes. Collaborating closely with data scientists and product teams, your role will focus on enhancing MLOps practices, ensuring high standards of security, performance, and compliance.Responsibilities• Build and maintain scalable feature pipelines within data lakehouse architectures.\n• Develop fallback feature flows and implement robust data quality checks.\n• Develop ranking, scoring, and entity-similarity models for the matching platform.\n• Use modern ML model frameworks such as PyTorch, TensorFlow, or XGBoost.\n• Apply SHAP or similar techniques to generate interpretable model explanations.\n• Build and maintain training, processing, and inference pipelines using AWS SageMaker.\n• Deploy and optimise low-latency, real-time inference endpoints.\n• Implement feature drift and concept drift monitoring.\n• Apply procedures for data handling, encryption, PII minimisation, and auditability.\n• Conduct validation of models using golden datasets and baseline tests.\nEssential Skills• Strong experience delivering production-grade ML systems.\n• Proficiency with AWS SageMaker, including training jobs and Model Registry.\n• Excellent skills with ML models like PyTorch, TensorFlow, or XGBoost.\n• Hands-on experience with model explainability tools such as SHAP.\n• Understanding of low-latency, real-time inference patterns.\n• experience in drift detection, monitoring, and telemetry.\n• Working knowledge of ML governance and secure ML practices.\n• Strong understanding of MLOps, CI/CD, and automation for ML workflows.\nAdditional Skills & Qualifications• experience with feature stores or Lakehouse data architectures.\n• Previous experience with ranking, matching, or similarity models.\n• Familiarity with cross-account AWS IAM patterns.\n• Bachelor's degree in a STEM subject such as mathematics, physics, engineering, or computer science.\nWhy Work Here?Join a forward-thinking company focused on innovation and excellence in machine learning. We provide a collaborative environment where your contributions directly impact the development of cutting-edge technology. Enjoy opportunities for professional growth and be part of a team dedicated to pioneering advancements in AI/ML.Work EnvironmentWork in a dynamic and collaborative environment leveraging state-of-the-art technologies. You will have access to modern tools and resources, including AWS SageMaker and various ML frameworks. Our flexible work culture promotes work-life balance and encourages continuous learning and development.\n\nLocation\nLondon, UK\n\nTrading as TEKsystems. Allegis Group Limited, Maxis 2, Western Road, Bracknell, RG12 1RT, United Kingdom. No. 2876353. Allegis Group Limited operates as an Employment Business and Employment Agency as set out in the Conduct of Employment Agencies and Employment Businesses Regulations 2003. TEKsystems is a company within the Allegis Group network of companies (collectively referred to as \"Allegis Group\"). Aerotek, Aston Carter, EASi, Talentis Solutions, TEKsystems, Stamford Consultants and The Stamford Group are Allegis Group brands. If you apply, your personal data will be processed as described in the Allegis Group Online Privacy Notice available at https://www.allegisgroup.com/en-gb/privacy-notices.\n\nTo access our Online Privacy Notice, which explains what information we may collect, use, share, and store about you, and describes your rights and choices about this, please go to https://www.allegisgroup.com/en-gb/privacy-notices.\n\nWe are part of a global network of companies and as a result, the personal data you provide will be shared within Allegis Group and transferred and processed outside the UK, Switzerland and European Economic Area subject to the protections described in the Allegis Group Online Privacy Notice. We store personal data in the UK, EEA, Switzerland and the USA. If you would like to exercise your privacy rights, please visit the \"Contacting Us\" section of our Online Privacy Notice at https://www.allegisgroup.com/en-gb/privacy-notices for details on how to contact us. To protect your privacy and security, we may take steps to verify your identity, such as a password and user ID if there is an account associated with your request, or identifying information such as your address or date of birth, before proceeding with your request. If you are resident in the UK, EEA or Switzerland, we will process any access request you make in accordance with our commitments under the UK Data Protection Act, EU-U.S. Privacy Shield or the Swiss-U.S. Privacy Shield.",
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  "job_posted_at_datetime_utc": "2026-03-26T00:00:00.000Z"
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