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    <title>Lead ML Engineer (SageMaker) - Teksystems RSS Feed</title>
    <link>https://jobs.co.uk/job/lead-ml-engineer-sagemaker-teksystems--ad617314-26b0-43f4-8ede-0987d79a92f8</link>
    <description>RSS feed for Lead ML Engineer (SageMaker) at Teksystems.</description>
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    <lastBuildDate>Wed, 22 Apr 2026 18:07:43 GMT</lastBuildDate>
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      <title>Lead ML Engineer (SageMaker) - Teksystems</title>
      <link>https://jobs.co.uk/job/lead-ml-engineer-sagemaker-teksystems--ad617314-26b0-43f4-8ede-0987d79a92f8</link>
      <guid>https://jobs.co.uk/job/lead-ml-engineer-sagemaker-teksystems--ad617314-26b0-43f4-8ede-0987d79a92f8</guid>
      <pubDate>Thu, 26 Mar 2026 00:00:00 GMT</pubDate>
      <description>Location: London | Salary: Negotiable | Type: Temporary | Job Title: Lead Machine Learning Engineer (SageMaker, MLOps, Explainability)   Job Description  We 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.  Develop fallback feature flows and implement robust data quality checks.  Develop ranking, scoring, and entity-similarity models for the matching platform.  Use modern ML model frameworks such as PyTorch, TensorFlow, or XGBoost.  Apply SHAP or similar techniques to generate interpretable model explanations.  Build and maintain training, processing, and inference pipelines using AWS SageMaker.  Deploy and optimise low-latency, real-time inference endpoints.  Implement feature drift and conce...</description>
      <category>Temporary</category>
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