Senior Data Scientist

7 days ago

Dubai, Dubai, United Arab Emirates ClickJobs Full time
About the Role

We are seeking a highly skilled Senior Machine Learning Engineer to join our team at ClickJobs. As a key member of our data science team, you will be responsible for designing, building, and delivering machine learning models and components that solve real-world business problems.

Key Responsibilities
  • Design and Development: Design, build, and deliver machine learning models and components that solve real-world business problems, working in collaboration with the Product and Data Science teams.
  • Infrastructure Decisions: Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation.
  • Problem-Solving: Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment.
  • Collaboration: Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications.
  • Model Maintenance: Retrain, maintain, and monitor models in production.
  • Cloud Architecture: Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale.
  • Data Pipelines: Construct optimized data pipelines to feed ML models.
  • Continuous Integration and Deployment: Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code.
  • Responsible and Explainable AI: Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI.
  • Programming Languages: Use programming languages like Python, Scala, or Java.
Requirements
  • Bachelor's Degree: Bachelor's degree in a relevant field.
  • Programming Experience: At least 4 years of experience programming with Python, Scala, or Java.
  • Data-Intensive Solutions: At least 3 years of experience designing and building data-intensive solutions using distributed computing.
  • ML Frameworks: At least 2 years of on-the-job experience with an industry-recognized ML framework (scikit-learn, PyTorch, Dask, Spark, or TensorFlow).
  • Productionizing Models: At least 1 year of experience productionizing, monitoring, and maintaining models.
Preferred Qualifications
  • Spark and Kubeflow: 1+ years of experience with Spark and Kubeflow or other pipeline orchestration technologies.
  • ML Systems: 1+ years of experience building, scaling, and optimizing ML systems.
  • Data Gathering and Preparation: 1+ years of experience with data gathering and preparation for ML models.
  • Developing Performant Code: 2+ years of experience developing performant, resilient, and maintainable code.
  • Public Cloud Experience: Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform.
  • Advanced Degree: Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field.
  • Distributed File Systems: 3+ years of experience with distributed file systems or multi-node database paradigms.
  • Open Source Contributions: Contributed to open source ML software.
  • Research Experience: Authored/co-authored a paper on a ML technique, model, or proof of concept.
  • Production-Ready Data Pipelines: 3+ years of experience building production-ready data pipelines that feed ML models.
  • Complex Data Pipelines: Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance.

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