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    Engineer - Data Engineer - Vancouver, BC, Canada - railtown

    railtown
    railtown Vancouver, BC, Canada

    1 week ago

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    Description

    As a Senior Machine Learning Engineer, you will work with our growing AI team in developing AI and machine learning (ML) solutions for problems in the software development domain.

    This position will provide a mix of research and engineering problems as you will be involved in the development of the end-to-end machine learning pipeline, ranging from data ingestion, wrangling, model development, to cloud deployment.

    This position will provide you the opportunity to develop and roll out innovative products using modern data science practice with both classical and state-of-the-art AI and ML models.

    As a fast-growing start-up, we cultivate an environment that will help you meet your full potential. Have strong analytical and problem-solving skills, and willing to dive deep to find creative solutions.
    Have a passion for developing new and innovative solutions with AI, machine learning, and statistical approaches.
    Formulate the business problem into AI and Machine Learning tasks
    Working with different types of data including computer logs, errors, natural languages, and more
    Extract, transform, load structured and unstructured text data
    Perform AI and machine learning experiments methodically, and conduct data and error analysis to improve models
    Collaborate with the engineering team to implement (build, test and deploy) the ML models
    Create unit, integration, end-to-end, and/or performance tests.
    Keep current with technology and industry developments and be on the lookout for new approaches and opportunities to integrate them into the existing solutions
    BSc or MSc degree in computer science, engineering, statistics, applied mathematics, or related quantitative discipline.
    Ability to synthesize information from multiple sources and act as thought leaders to design creative solutions.
    Experience in ML/AI solution architecture is an asset.
    Strong track records in building MLOps and productionizing ML/AI solutions in Azure cloud (or AWS). Experience in data mining, machine learning, and/or statistical analysis. Knowledge of NLP approaches is an asset.
    Strong experience in Python and knowledge of SQL is a plus.
    Familiarity with modern machine learning packages such as NumPy, SciPy, Pandas, Matplotlib, seaborn, Scrapy, scikit-learn, etc. Experience with Deep Learning packages such as Pytorch or TensorFlow is an asset.
    Knowledge of the Cross Industry Standard Process for Data Mining(CRISP-DM) or similar data-science lifecycle.
    Experience building custom integrations between cloud-based systems using APIs.
    Basic knowledge of agile software development (e.g. version control, kanban processes, and cloud deployment).
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