5G RAN Machine Learning Engineer

Senior 5G RAN Machine Learning Engineer
Duration: 6 Months (Contract)
Employment Type: W2 Only
Pay Rate: Up to $70/hr on W2

Job Summary:

We are seeking a Senior 5G RAN Machine Learning Engineer to join a high-performing wireless network analytics team. The ideal candidate will have strong expertise in Machine Learning, Data Science, Python, Spark, and Telecom (4G/5G RAN) to develop predictive models, analyze large-scale network performance data, and support AI-driven decision-making.

Required Qualifications

• 7+ years of experience in Data Science, Machine Learning, Data Analytics, or Data Engineering

• Strong programming skills in Python, SQL, and Spark/PySpark

• Experience with Machine Learning, Predictive Modeling, and Statistical Analysis

• Strong knowledge of Data Modeling and handling large datasets

• Experience with cloud platforms such as AWS, Azure, Google Cloud Platform, Databricks, or Snowflake

• Experience with Linux and Git-based version control

• Excellent analytical and communication skills

Preferred Qualifications

• Experience in 4G LTE, 5G NR, RAN, RF, OSS, or Wireless Network Performance

• Knowledge of telecom KPIs/KQIs and network analytics

• Experience with MLOps, MLflow, Docker, Kubernetes, or Hadoop ecosystems

• Familiarity with Time Series Forecasting, Decision Trees, Random Forest, Neural Networks, Clustering, PCA, and Regression Models

Responsibilities

• Develop and deploy Machine Learning models for wireless network performance analysis

• Analyze large-scale telecom datasets to identify trends and performance issues

• Build predictive analytics models and automation solutions

• Collaborate with RF, Network, and Data Science teams

• Create dashboards and visualizations to communicate business insights

• Support AI-driven optimization of 4G/5G network performance

Preferred BackgroundCandidates with experience supporting wireless carriers or telecom equipment providers such as Ericsson, Nokia, Mavenir, Verizon, AT&T, T-Mobile, DISH, Qualcomm, or similar environments are highly encouraged to apply.