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Remote Nvidia Machine Learning Jobs in Virginia (NOW HIRING)

Vienna, VA and Chantilly, VA with remote flexibility Responsibilities: As a Machine Learning Engineer, you'll be part of the Agile team delivering machine learning applications and software systems ...

Vienna, VA and Chantilly, VA with remote flexibility Responsibilities: As a Machine Learning Engineer, you'll be part of the Agile team delivering machine learning applications and software systems ...

Vienna, VA and Chantilly, VA with remote flexibility Responsibilities: As a Machine Learning Engineer, you'll be part of the Agile team delivering machine learning applications and software systems ...

Vienna, VA and Chantilly, VA with remote flexibility Responsibilities: As a Machine Learning Engineer, you'll be part of the Agile team delivering machine learning applications and software systems ...

Machine Learning Engineer - Remote

Vienna, VA ยท On-site +1

$140K - $150K/yr

Halvik is a highly successful WOB business with more than 50 prime contracts and 500+ professionals delivering Digital Services, Advanced Analytics, Artificial Intelligence/Machine Learning ...

Remote Work: Niyam understands the value of flexibility. We offer remote work. * Career Growth ... The ideal candidate brings a strong foundation in machine learning, data engineering, and MLOps ...

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Remote Nvidia Machine Learning information

Can you work for NVIDIA remotely?

Remote Nvidia machine learning roles are available, with many positions allowing employees to work from home depending on the team and project requirements. Candidates typically need strong technical skills in machine learning, experience with Nvidia tools like CUDA, and may require specific certifications or hardware setup for remote work. Availability varies by role and location policies.

Which 5 jobs will survive AI?

Remote Nvidia Machine Learning roles are likely to persist as they require specialized skills in AI, deep learning, and GPU programming. Jobs involving complex problem-solving, creativity, and human interaction, such as data scientists, AI researchers, software engineers, cybersecurity specialists, and technical trainers, are expected to remain in demand despite AI advancements.

How much do NVIDIA machine learning engineers make?

NVIDIA machine learning engineers typically earn between $100,000 and $160,000 annually, depending on experience, location, and skill level. Senior roles or those with specialized expertise in deep learning and GPU programming can earn higher salaries, often exceeding $180,000. Compensation may also include bonuses and stock options in competitive tech environments.

Is it difficult to get hired at NVIDIA?

Getting hired for a remote Nvidia machine learning role can be competitive due to the company's high standards and specialized skill requirements. Candidates typically need strong expertise in machine learning, deep learning frameworks, and relevant programming languages, along with a solid educational background. Demonstrating experience with Nvidia technologies and certifications can improve chances of selection.

What is the difference between Remote Nvidia Machine Learning vs Remote Data Scientist?

AspectRemote Nvidia Machine LearningRemote Data Scientist
Required CredentialsDeep learning, GPU programming, Nvidia certificationsStatistics, programming, data analysis
Work EnvironmentFocus on GPU-accelerated ML models, Nvidia toolsData analysis, modeling, visualization
Industry UsageAI, autonomous vehicles, gaming, HPCBusiness analytics, research, finance

Remote Nvidia Machine Learning specialists focus on developing GPU-accelerated AI models using Nvidia technologies, often requiring specific certifications and expertise in GPU programming. In contrast, Remote Data Scientists analyze data, build predictive models, and interpret results across various industries. While both roles involve data and programming skills, Nvidia Machine Learning roles are more specialized in GPU-based AI development, whereas Data Scientists have broader data analysis responsibilities.

What are the most commonly searched types of Nvidia Machine Learning jobs in Virginia? The most popular types of Nvidia Machine Learning jobs in Virginia are:
What cities in Virginia are hiring for Remote Nvidia Machine Learning jobs? Cities in Virginia with the most Remote Nvidia Machine Learning job openings:
Senior Wireless Machine Learning Engineer, AI-RAN

Senior Wireless Machine Learning Engineer, AI-RAN

DeepSig Inc

Arlington, VA โ€ข On-site, Remote

Other

Posted 9 days ago


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.