Machine Learning Engineer

  • Posted 18 hours ago | Updated 17 hours ago

Overview

Remote
Accepts corp to corp applications
Contract - long term

Skills

Data Modeling
SQL
Database Modeling
Business Intelligence
Business Requirements
Version Control
SQL Queries
Documentation
Stored Procedures
GCP
Power Bi
data visualization
BigQuery
google cloud
Data Services
Translate
Governance
Microstrategy
User Experience
Gather Requirements

Job Details

Machine Learning Engineer Experience: 5+ Years Location: Remote

What's in it for you?

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.

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.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.