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Remote Ran Optimization Engineer Jobs in Washington, DC

Remote Job Overview We are seeking experienced CUDA Engineering Experts to support a cutting-edge GPU optimization project. You will apply your expertise in CUDA, C++, and GPU programming to analyze ...

Remote Job Overview We are seeking experienced CUDA Engineering Experts to support a cutting-edge GPU optimization project. You will apply your expertise in CUDA, C++, and GPU programming to analyze ...

Remote Job Overview We are seeking experienced CUDA Engineering Experts to support a cutting-edge GPU optimization project. You will apply your expertise in CUDA, C++, and GPU programming to analyze ...

GPU Programmer - Remote Job Type: Contractor Location: Remote Job Overview We are seeking ... You will apply your expertise in GPU programming, performance optimization, and C++ development to ...

No Overtime Pay Basis Remote (within USA - W/ On-Site Meetings Expected) in The CONUS - Located In ... Production optimization, field operations, artificial lift, throughput, and production performance ...

... Engineer with 6-8 years of experience to join our AI applications team. This is a fully remote ... Performance Optimization: Review and analyze software runtime performance, making algorithmic and ...

General information Job Posting Title Lead Security Engineer - Remote Date Wednesday, August 12 ... and optimization. - Lead or actively contribute to other information security projects and ...

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Remote Ran Optimization Engineer information

See Washington, DC salary details

$46

$67

$92

How much do remote ran optimization engineer jobs pay per hour?

As of Aug 29, 2026, the average hourly pay for remote ran optimization engineer in Washington, DC is $67.56, according to ZipRecruiter salary data. Most workers in this role earn between $48.99 and $83.32 per hour, depending on experience, location, and employer.

What is the difference between Remote Ran Optimization Engineer vs Radio Network Optimization Engineer?

AspectRemote Ran Optimization EngineerRadio Network Optimization Engineer
CredentialsTypically requires a degree in telecommunications, certifications like Nokia, Ericsson, or vendor-specific trainingSimilar credentials, often with certifications in radio network design and optimization
Work EnvironmentPrimarily remote, collaborating with teams across locations, using remote toolsUsually onsite or hybrid, with field visits for testing and adjustments
Industry UsageCommon in telecom providers, network vendors, and remote service providersUsed in telecom companies, network operators, and infrastructure firms

Both roles focus on optimizing radio networks, but the Remote Ran Optimization Engineer emphasizes remote work and virtual collaboration, while the Radio Network Optimization Engineer may involve more onsite activities. Both require similar technical skills and certifications, with the main difference being the work environment.

What are popular job titles related to Remote Ran Optimization Engineer jobs in Washington, DC?

For Remote Ran Optimization Engineer jobs in Washington, DC, the most frequently searched job titles are:

What job categories do people searching Remote Ran Optimization Engineer jobs in Washington, DC look for?

The top searched job categories for Remote Ran Optimization Engineer jobs in Washington, DC are:

Infographic showing various Remote Ran Optimization Engineer job openings in Washington, DC as of August 2026, with employment types broken down into 92% Full Time, 2% Part Time, and 6% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $140,518 per year, or $67.6 per hour.

Senior Wireless Machine Learning Engineer, AI-RAN

DeepSig Inc

Arlington, VA • On-site, Remote

Full-time

Posted 3 days ago

New


Job description

Description

Type: Full-Time(W2) On-site/Hybrid, Arlington, VA (Remote option available for the right candidate)


DeepSig is defining the future of wireless communications by merging deep learning with the Radio Access Network (RAN). We are seeking an experienced Technical Lead to architect and drive the development of our next-generation AI-native RAN.


In this role, you will design, prototype, and validate novel AI/ML components-such as neural receivers, neural beamforming, neural scheduling, digital twin, and ISAC (Integrated Sensing and Communications)-that outperform traditional signal processing methods. You will work at the cutting edge of 6G innovation, taking concepts from mathematical intuition to simulation (e.g. NVIDIA Sionna) and real-time implementation.


What You'll be Doing 

  • Applied AI Research: Design and train modern deep learning models (Transformers, Vision architectures, etc.) to solve complex physical layer problems, including channel estimation, MIMO detection, and beam management
  • Simulation & Validation: Build high-fidelity link-level simulations using NVIDIA Sionna and ray-tracing to train, test, and benchmark AI models against legacy 5G baselines
  • Prototyping & Deployment: Transition research models into deployable "dApps" for the Distributed Unit (DU), optimizing inference for latency and compute efficiency on NVIDIA GPUs
  • New Capabilities: Explore emerging AI-RAN frontiers such as Integrated Sensing and Communications (ISAC), neural scheduling, and channel digital twins
  • Innovation & IPR: Drive technical innovation by authoring invention disclosures, filing patents, and generating technical reports to support our standardization team in 3GPP and O-RAN Alliance contributions
  • Data Engineering: Architect data pipelines for generating synthetic training datasets and developing "Sim-to-Real" transfer techniques to ensure robust performance in real-world networks

Required Qualifications

  • Education: Ph.D. or Master's in Computer Science, Electrical Engineering, or Applied Mathematics with a focus on Deep Learning and/or Communications Systems
  • AI/ML Expertise: 3+ years of experience designing and training deep neural networks from scratch. Strong grasp of modern architectures and optimization techniques
  • Applied Signal Processing: Experience applying machine learning to real-time time-series data, signal processing, or physics-based problems (Audio, RF, or similar domains)
  • Research to Code: Proven ability to read academic papers and implement their methods in robust Python code
  • Simulation Skills: Experience with differentiable simulation or digital twins (e.g., Sionna, JAX-based physics sims)

Preferred Qualifications

  • Wireless Knowledge: Understanding of wireless fundamentals (OFDM, MIMO, IQ data) is highly helpful, though we prioritize strong ML intuition over pure communication theory
  • Performance Optimization: Experience with model quantization (FP16/INT8), pruning, or using TensorRT for real-time inference
  • Standardization Support: Experience writing technical whitepapers or supporting patent filings in a research environment
  • C++ Integration: Ability to write C++ bindings or integrate Python models into C++, SIMD, and Cuda production pipelines

Working at DeepSig

DeepSig is growing its technical team while cultivating a collaborative, agile, and fun small-team culture. We value creativity, knowledge sharing, and employee growth, and we encourage participation in scientific publications, conferences, and open-source software. We offer competitive salaries and benefits, an employee stock option grant program, an environment where we are excited to be transforming and disrupting how signal processing is done with AI/ML, a welcoming and inclusive environment, a flexible schedule, and a great work / life balance.


DeepSig is an equal-opportunity employer and does not discriminate based on race, ethnicity, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability. We are dedicated to cultivating an inclusive, diverse, and engaging workplace where individuals feel fulfilled, inspired, and motivated. We value the unique perspectives that our team brings.