Microsoft Azure ML Engineer - City of Edinburgh - Version 1 Group

    Version 1 Group
    Version 1 Group City of Edinburgh

    1 week ago

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    Description

    About Us

    We are a trusted technology services company with over 26 years of experience. We deliver solutions that drive customer success for global brands, and we're proud to be an award-winning employer.

    We've been recognised for our innovation and commitment to excellence, including the Innovation Partner of the Year Award at the Oracle EMEA Partner Awards 2023 and the Global Microsoft Modernising Applications Partner of the Year Award 2023.

    Our Values

    We're a digital-first environment, and we do things differently. Our core values guide everything we do, and they've enabled us to achieve significant growth across our practices.

    Job Description

    1. Apply Machine Learning Techniques: Use machine learning, deep learning, natural language processing, computer vision, and other AI techniques to analyse large datasets and extract meaningful patterns and insights.
    2. Data Exploration: Explore and pre-process raw data to uncover trends, anomalies, and patterns.
    3. Visualisation: Create clear and compelling visualisations to communicate findings to both technical and non-technical stakeholders.
    4. Model Evaluation: Evaluate and optimise the performance, accuracy, and scalability of AI models and systems.
    5. Research and Development: Research and implement state-of-the-art AI methods and best practices.
    6. Collaboration: Collaborate with cross-functional teams of engineers, product managers, designers, and stakeholders to understand business requirements and formulate data-driven solutions.
    7. Domain Expertise: Collaborate with domain experts to integrate domain knowledge into analytical models.
    8. Prototype and Test: Prototype, test, and productionise machine learning models. Monitor and optimise model performance over time.
    9. Data Modelling: Model data for storage and querying in database and large-scale analytics platforms.
    10. Variety of Data Types: Work with a wide variety of data types, from structured to unstructured, multimedia (video and still images), time-series and IoT data.
    11. Communication: Clearly visualise and communicate processes and results to clients, colleagues, and other stakeholders.
    12. Team Support: Support more junior colleagues and help develop the capabilities of the team.
    13. Specialist Knowledge: Work with colleagues across the firm to apply data science principles to specialist areas of the client's business.

    Qualifications

    • Hands-on experience with using, configuring, and migrating ML models to Azure ML specifically a Kubeflow/Tensorflow stack (on prem) to a full managed Azure ML solution.
    • A passion for developing and communicating deep and valuable insights.
    • A highly rigorous mindset and approach to your work.
    • In-depth knowledge of statistics and research methodology/experimental design.
    • Extensive, demonstrable experience building and testing/validating machine learning models and using data mining techniques.
    • Extensive experience of data modelling and database design.
    • Demonstrable programming experience in Python and associated data science/ML libraries in Azure ML Tech Stack.
    • The ability to form clear narratives that communicate complex ideas to diverse audiences.
    • Experience of team leadership/supervising others.
    • Experience of proposal writing, project costing, project management, etc.
    • Ability to quickly make sense of new topics in unfamiliar fields.
    • Specialist experience in a particular domain/application of data science, e.g. natural language processing, remote sensing, IoT.
    • A Bachelor or Master degree in a computational field (Computer Science, Applied Mathematics, Engineering, or in a related quantitative discipline).
    • Azure Certified Machine Learning Certification would be desirable.

    Additional Information

    We offer a comprehensive benefits package that prioritises employee well-being, professional growth, and financial stability. This includes a hybrid schedule, business travel opportunities, tech-related benefits, private medical and life insurance coverage, and career development support.

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