Machine Learning Engineer - New York, NY

  • New York, NY
  • Posted 7 days ago | Updated 7 days ago

Overview

On Site
Depends on Experience
Contract - W2
Contract - Independent

Skills

Algorithms
Amazon Web Services
Apache Hadoop
Applied Mathematics
Artificial Intelligence
Big Data
Cloud Computing
Collaboration
Communication
Computer Science
Data Science
Deep Learning
Design Of Experiments
Good Clinical Practice
Google Cloud Platform
Machine Learning (ML)
Microsoft Azure
NumPy
Pandas
PySpark
PyTorch
Python
Scalability
Statistical Models
Statistics

Job Details

Title: Machine Learning Engineer
Location: New York, NY (Hybrid, 2-3 days onsite)
Rate: DOE $/HR

Job Description:

  • Analyze large and complex datasets to extract insights and drive business decisions.

  • Develop and deploy machine learning models to solve real-world problems.

  • Collaborate with cross-functional teams to understand business needs and provide data-driven solutions.

  • Optimize ML models for performance and scalability in a production environment.

  • Stay updated with the latest advancements in machine learning and AI technologies.

Basic Qualifications:

  • Bachelor s degree in Computer Science, Statistics, Applied Mathematics, or a related field.

  • Minimum 5 years of experience in a data science or machine learning role.

  • Proficiency in Python and ML libraries (Pandas, NumPy, Scikit-Learn, PySpark).

  • Strong understanding of ML techniques, algorithms, and statistical modeling.

Preferred Qualifications:

  • Experience with deep learning frameworks (PyTorch, TensorFlow).

  • Hands-on experience with big data technologies (PySpark, Hadoop).

  • Experience deploying ML models on cloud platforms (AWS, Azure, Google Cloud Platform).

  • Strong communication skills to present insights to non-technical stakeholders.

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.