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Entry Level Ran Optimization Engineer Jobs in Edison, NJ

MedReview

ETL Engineer

Manhattan, NY · On-site

$120/hr

This is not an entry-level role. You will be working with modern data tools and large datasets ... Strong SQL skills (writing, optimizing, and troubleshooting complex queries) * Experience working ...

MedReview

ETL Engineer

Manhattan, NY · On-site

This is not an entry-level role. You will be working with modern data tools and large datasets ... Strong SQL skills (writing, optimizing, and troubleshooting complex queries) * Experience working ...

SKF Group

Product Design Engineer

New York, NY

$141.10K - $169.60K/yr

... manufacture, optimization of our multimillion-dollar Heat Treatment facility as well as ... We are seeking an experienced professional, but we will also consider entry-level applicants with ...

Latech Apps

Junior frontend developer

New York, NY · On-site +1

$73.30K - $95.20K/yr

Junior frontend developer We are looking for a motivated Junior Frontend Developer to join our ... O principles and web accessibility standards (WCAG). What We Offer Competitive entry-level salary ...

MACARO IRON WORKS LLC

Estimator

Manville, NJ · On-site

$18.50 - $27/hr

This is not an entry-level role. You will be responsible for producing accurate takeoffs and ... Support value engineering and cost optimization when needed Requirements (Must-Have) * Minimum 2 ...

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Entry Level Ran Optimization Engineer information

See Edison, NJ salary details

$31.1K

$71.8K

$122.2K

How much do entry level ran optimization engineer jobs pay per year?

As of May 31, 2026, the average yearly pay for entry level ran optimization engineer in Edison, NJ is $71,807.00, according to ZipRecruiter salary data. Most workers in this role earn between $53,300.00 and $81,300.00 per year, depending on experience, location, and employer.

What is the difference between Entry Level Ran Optimization Engineer vs Network Optimization Technician?

AspectEntry Level Ran Optimization EngineerNetwork Optimization Technician
CredentialsBachelor's in Telecommunications, Electrical Engineering, or related fieldAssociate's or Bachelor's in Networking, Telecommunications, or related field
Work EnvironmentTelecom companies, network providers, field and office settingsTelecom companies, network service providers, field and lab environments
Industry UsageCommonly used in mobile network planning and optimizationUsed in maintaining and troubleshooting network performance

Entry Level Ran Optimization Engineers focus on optimizing radio access network parameters to improve coverage and capacity, often working with LTE/5G networks. Network Optimization Technicians handle network performance issues, troubleshooting, and maintenance. While both roles require telecommunications knowledge, the Engineer role emphasizes planning and optimization, whereas Technicians focus on operational support and problem resolution.

What are popular job titles related to Entry Level Ran Optimization Engineer jobs in Edison, NJ? For Entry Level Ran Optimization Engineer jobs in Edison, NJ, the most frequently searched job titles are:
What job categories do people searching Entry Level Ran Optimization Engineer jobs in Edison, NJ look for? The top searched job categories for Entry Level Ran Optimization Engineer jobs in Edison, NJ are:
Entry Level Ran Optimization Engineer jobs near you
Infographic showing various Entry Level Ran Optimization Engineer job openings in Edison, NJ as of May 2026, with employment types broken down into 94% Full Time, and 6% Part Time. Highlights an 82% In-person, 12% Hybrid, and 6% Remote job distribution, with an average salary of $71,807 per year, or $34.5 per hour.

Wireless O-RAN AI/ML Engineer (PhD is required)

Innovatix Technology Partners

Bedminster, NJ

Other

Posted 10 days ago

Job description

We are seeking a talented and motivated Wireless Research Engineer with strong software and AI/ML capabilities to join our advanced networking team. Instead of traditional network deployment, this role sits at the cutting edge of Next-Gen cellular architecture: Open RAN (O-RAN).

In this role, you will apply your foundational knowledge of wireless communications to design, simulate, and develop intelligent solutions for Near-Real-Time (Near-RT) and Non-Real-Time (Non-RT) RAN Intelligent Controllers (RIC). You will leverage your coding skills in Python, alongside machine learning frameworks, to build the xApps and rApps that drive automation and optimize 5G network performance. This is the perfect launchpad for a telecom graduate eager to build software-driven, intelligent wireless infrastructure.

Key Responsibilities

  • Wireless Modeling & Simulation: Collaborate with senior engineers on system-level wireless simulations, network modeling, and cellular prototype testing.
  • App Development (xApps/rApps): Develop, test, and integrate intelligent xApps (Near-RT RIC) and rApps (Non-RT RIC) to control radio resources using Python.
  • RAN Optimization via AI/ML: Apply machine learning frameworks to solve telecom-specific challenges such as radio resource management (RRM), beamforming, traffic steering, and interference mitigation.
  • Telecom Data Analytics: Process and analyze large streams of live RAN telemetry and network KPI data using SQL database.
  • Standards Alignment: Study and implement O-RAN Alliance specifications to ensure prototype solutions align with evolving industry standards.

Required Skills & Qualifications

  • Education: PhD in Electrical Engineering, Telecommunications Engineering, or a closely related field with a heavy focus on wireless systems.
  • Wireless Deep Dive: A rock-solid foundational understanding of Wireless Communications, cellular network architecture (4G/5G), and radio frequency (RF) or protocol layer concepts.
  • O-RAN & RIC Exposure: Strong academic familiarity or project work involving O-RAN architecture, RIC platforms, and split-architecture concepts.
  • Programming & Software: High proficiency in Python, with the ability to write clean, structured code for network applications.
  • AI/ML Application: Hands-on experience (via academic research, capstone projects, or internships) applying ML libraries like TensorFlow or PyTorch to solve engineering or signal processing problems.
  • Data Basics: Familiarity with managing data via SQL and exposure to containerized environments (Docker/Kubernetes).

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