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Machine Learning Engineer jobs

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  1. Principal AI Engineer

    Posted yesterday by Granite Consulting

    Remote job Quick apply
    Salary:
    £80,000 - £130,000/annum
    Location:
    BS1, Bristol, City of Bristol
    Job Type:
    Permanent

    Principal AI Engineer – £80,000 - £130,000 + bonus + private healthcare. Bristol / work from home hybrid. An excellent opportunity for a Principal AI Engineer to join one of Bristol's fastest growing software houses. The role will play the central role in implementing AI and … more

  2. Senior Engineer- Data & Infra

    Posted yesterday by Hays Technology

    Remote job
    Salary:
    £50,000 - £60,000/annum £50-60k DOE
    Location:
    Gloucestershire
    Job Type:
    Permanent

    Collaborate with Data Scientists and Machine Learning Engineers to construct analytics tools that leverage the data pipeline. These tools provide actionable insights related to asset management, operational efficiency, and other critical business metrics. Cross-Functional … more

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  3. Data Scientist (DV Security Clearance)

    Posted today by CGI

    Location:
    Gloucester
    Job Type:
    Permanent

    Experience as a Data Scientist, demonstrating an excellent understanding of standard data scientists responsibilities such as machine learning techniques, algorithms, statistics, visualisation etc. Experience with common data science toolkits and core skills in one of Python, NumPy … more

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  4. Lead Solutions Engineer (Associate Director)

    Posted yesterday by Simple Machines

    Salary:
    £NEG
    Location:
    London
    Job Type:
    Permanent

    Principal Solutions Engineer (Associate Director.. Simple Machines is seeking a Principal Solutions Engineer (Associate Director) to become a part of our team. This full-time position is located in London and entails working as a consultant engineer on the … more

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  5. Senior Data Scientist

    Posted yesterday by Vitality

    Featured job
    Location:
    London
    Job Type:
    Permanent

    Implementing the machine learning life cycle: building models in a structured manner following best practice in the collection and analysis of modelling data, feature engineering, model fitting, selection, evaluation, deployment, and monitoring. Delivering high impact … more

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