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Ran Optimization Jobs in Virginia (NOW HIRING)

DevOps Engineer

Arlington, VA ยท On-site

$60.75 - $83.25/hr

... RAN). We are seeking an experienced DevOps Engineer to work with engineering and QA teams to ... Optimization : Optimize the utilization of CI/CD and compute infrastructure in collaboration with ...

DevOps Engineer

Arlington, VA ยท On-site

$60.75 - $83.25/hr

... RAN). We are seeking an experienced DevOps Engineer to work with engineering and QA teams to ... Optimization : Optimize the utilization of CI/CD and compute infrastructure in collaboration with ...

DevOps Engineer

Arlington, VA ยท Hybrid

$60.75 - $83.25/hr

... RAN). We are seeking an experienced DevOps Engineer to work with engineering and QA teams to ... Optimization : Optimize the utilization of CI/CD and compute infrastructure in collaboration with ...

This role involves developing DSP, optimizing the physical layer procedures, and implementing ... RAN development to drive innovation in next-generation satellite-based mobile networks. Core ...

$81K - $87K/yr

Salary Ran ge: $81,000.00 - 87,000.00 Actual pay depends on specialty, experience, and performance ... pathway optimization. * Ensure compliance with all hospital, medical group, state, and federal ...

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Ran Optimization information

What is RAN Optimization?

RAN Optimization refers to the process of improving the performance and efficiency of a Radio Access Network (RAN), which is a crucial part of mobile communication systems. It involves analyzing network data, identifying issues such as coverage gaps, dropped calls, or slow data speeds, and implementing solutions to enhance user experience and network capacity. RAN Optimizers use specialized tools to monitor network performance, adjust configurations, and recommend upgrades. This role is essential for maintaining high-quality wireless services as network demands grow and technologies evolve.

What are the key skills and qualifications needed to thrive as a RAN Optimization engineer?

To thrive as a RAN Optimization Engineer, you need strong knowledge of radio access network (RAN) technologies, cellular communications, and typically a degree in telecommunications or electrical engineering. Proficiency in tools such as TEMS, Actix, and network management systems, as well as relevant certifications like CCNA or 5G-related credentials, is often required. Analytical thinking, problem-solving, and effective communication are crucial soft skills for identifying network issues and collaborating with cross-functional teams. These skills ensure optimal network performance, efficient troubleshooting, and high-quality service for mobile network users.

What are some of the most common challenges faced by professionals in RAN Optimization, and how can they be addressed?

One of the most common challenges in RAN Optimization is balancing network performance with resource constraints, as optimizers must enhance coverage and capacity without causing interference. Additionally, adapting to rapid technological changes, such as 5G rollouts, requires continuous learning and flexibility. Effective collaboration with cross-functional teams, including RF engineers and network planners, is essential to implement optimization strategies that align with overall business goals. Staying updated on the latest tools and best practices, as well as proactively analyzing network data, can help professionals address these challenges successfully.

What is the difference between Ran Optimization vs Network Optimization?

AspectRan OptimizationNetwork Optimization
FocusOptimizing radio access network parameters for better coverage and performanceImproving overall network efficiency, including core and access networks
CredentialsTelecom engineering certifications, LTE/5G knowledgeTelecom engineering certifications, network architecture expertise
Work EnvironmentCell sites, radio network equipment, field and lab settingsNetwork operations centers, data analysis, planning offices
Industry UsageMobile carriers, telecom service providersMobile carriers, telecom infrastructure companies

While both roles involve optimizing network performance, Ran Optimization specifically targets radio access network parameters to enhance coverage and user experience. Network Optimization has a broader scope, focusing on overall network efficiency, including both radio and core network components. Professionals often work together but specialize in different areas of telecom network performance improvement.

What are popular job titles related to Ran Optimization jobs in Virginia?

For Ran Optimization jobs in Virginia, the most frequently searched job titles are:

What cities in Virginia are hiring for Ran Optimization jobs?

Cities in Virginia with the most Ran Optimization job openings:

Senior Wireless Machine Learning Engineer, AI-RAN

DeepSig Inc

Arlington, VA โ€ข 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 Doingย 

  • 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.