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Machine Learning Engineer

Machine Learning Engineer

VeeRteq Solutions LLCWashington, DC, United States
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Experience : 5+ Years Location : Remote

As a Machine Learning Engineer , you will work as part of an Agile team to build cutting-edge healthcare applications and implement new features while following industry best practices and coding standards.

What's in it for you?

Responsibilities

  • Partner with business stakeholders to identify opportunities for automating business processes using Machine Learning and AI.
  • Collaborate with project managers, DevOps, and engineering teams to coordinate model development, deployment, and monitoring.
  • Design, develop, and optimize machine learning models and algorithms for various business use cases.
  • Analyze complex datasets to extract actionable insights and build predictive models.
  • Write clean, efficient, and scalable code using Python, Spark, Scala, R, and Java.
  • Deploy ML models into production using CI / CD pipelines and containerization tools.
  • Continuously monitor and maintain model performance, implementing retraining as necessary.
  • Deliver analytics solutions and insights to clients, enabling data-driven decision-making.
  • Build dashboards and visualizations using Tableau to effectively communicate insights.
  • Leverage cloud ML platforms (AWS SageMaker, Azure ML, or Google Cloud AI) for scalable model development.
  • Follow best practices in version control, testing, and documentation using Git and shell scripting.
  • Ensure adherence to robust software architecture and data modeling standards.

Required Skills

  • Proven experience as a Machine Learning Engineer or in a similar role.
  • Strong understanding of data structures, data modeling, and software architecture.
  • Deep knowledge of mathematics, probability, statistics, and machine learning algorithms.
  • Proficiency in programming languages : Python, Spark, Scala, R, Java.
  • Hands-on experience with ML frameworks : TensorFlow, PyTorch, Keras, scikit-learn.
  • Familiarity with Docker, shell scripting, and Git.
  • Experience deploying ML models in production environments.
  • Experience with cloud ML platforms (AWS, Azure, or Google Cloud).
  • Excellent communication and collaboration skills.
  • Strong analytical and problem-solving abilities.
  • Preferred Skills

  • Experience with MLOps tools and practices.
  • Exposure to real-time data processing and streaming technologies.
  • Experience with data visualization tools like Tableau.
  • Direct experience working with clients to deliver analytics solutions.
  • Educational Qualifications

  • Master's Degree
  • Technical certifications in multiple technologies are desirable.
  • #J-18808-Ljbffr

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