Sr Data Engineer

3 months ago

Charlotte, United States Randstad Digital Full time

Machine Learning - Data Engineer

Roles/Responsibilities:

  • Work closely with data scientists, software engineers, product managers, and stakeholders to understand the requirements, challenges, and opportunities of machine learning projects.
  • Design, build, and maintain scalable and reliable data pipelines and platforms that support the development and deployment of machine learning models and applications.
  • Apply best practices and tools to ensure the quality, reliability, scalability, and security of machine learning pipelines and systems.
  • Optimize the performance, efficiency, and reliability of the data pipelines and platforms.
  • Monitor and troubleshoot the data pipelines and platforms and resolve any issues or errors.
  • Document and maintain development standards, best practices, and procedures.
  • Continuously learn and improve your skills and knowledge in the fast-changing field of machine learning.

Qualifications:

  • Bachelor's degree in computer science, engineering, mathematics, statistics, or related field.
  • At least 3 years of experience in machine learning, data engineering, or software engineering.
  • Proficient in Python and one or more of the following frameworks: TensorFlow, PyTorch, Scikit-learn, Keras, etc.
  • Familiar with programming languages such as Java, Scala.
  • Experience with data processing and storage technologies such as Spark, Hadoop, SQL, NoSQL, etc.
  • Experience with cloud computing platforms and services such as AWS, Azure, GCP, etc.
  • Experience with AWS SageMaker, AWS Glue, AWS EMR is a plus.
  • Experience with machine learning lifecycle management tools such as MLflow, Kubeflow, Airflow, etc.
  • Experience with containerization and orchestration technologies such as Docker, Kubernetes, etc.
  • Experience with version control, testing, and CI/CD tools such as Git, GitHub, Jenkins, etc.
  • Knowledge of machine learning concepts and techniques such as supervised, unsupervised, and reinforcement learning, deep learning, natural language processing, computer vision, etc.
  • Ability to communicate effectively and collaborate with cross-functional teams.
  • Ability to work independently and creatively, and solve complex problems.
  • Passion for learning and innovation.

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