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ML Engineer - REMOTE
ML Engineer - REMOTEPEOPLE FORCE CONSULTING INC • United States
ML Engineer - REMOTE

ML Engineer - REMOTE

PEOPLE FORCE CONSULTING INC • United States
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Role : ML Engineer

Location : REMOTE

As an ML Engineer , you will be a part of an Agile team to build healthcare applications and implement new features while adhering to the best coding development standards .

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 in production environments using CI / CD pipelines and containerization tools.
  • Monitor and maintain model performance, retraining as needed.
  • Deliver analytics solutions and insights to clients, supporting data-driven decision-making.
  • Create dashboards and visualizations using Tableau to communicate insights effectively.
  • Utilize cloud ML platforms such as AWS SageMaker, Azure ML, or Google Cloud AI for scalable model development.
  • Apply best practices in version control, testing, and documentation using Git and shell scripting.
  • Ensure robust software architecture and data modeling practices are followed.

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.
  • Experience with ML frameworks and libraries : TensorFlow, PyTorch, Keras, scikit-learn.
  • Familiarity with Docker, shell scripting, and Git.
  • Experience deploying ML models in production environments.
  • Hands-on experience with cloud ML platforms such as 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.
  • Experience working directly with clients to deliver analytics solutions.
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    Ml Engineer • United States

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