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Assistant Cuda Jobs in Reston, VA (NOW HIRING)

GDIT

Data Scientist - TS/SCI w/Poly

Mclean, VA · On-site

$212K - $287K/yr

Optimize existing machine learning services to better utilize current GPU capabilities and assist ... Python, Cuda, Kubernetes, CI/CD. Apache Kafka, REST architecture, Open-AI, LLMs, NLP, YOLO/Object ...

Parsons

Software Developer - TS/SCI

Chantilly, VA · On-site

Senior members at BRE also directly assist with winning new work, writing proposals, and ... CUDA/GPU, Grid Systems, Parallel Processing, Threading * An active TS/SCI w/polygraph is preferred ...

Parsons

Senior Software Developer - TS/SCI

Herndon, VA · On-site

$56 - $74/hr

Senior members at BRE also directly assist with winning new work, writing proposals, and ... CUDA/GPU, Grid Systems, Parallel Processing, Threading * An active TS/SCI w/polygraph is preferred ...

Parsons

Senior Software Developer - TS/SCI

Chantilly, VA · On-site

$55.75 - $73.75/hr

Senior members at BRE also directly assist with winning new work, writing proposals, and ... CUDA/GPU, Grid Systems, Parallel Processing, Threading * An active TS/SCI w/polygraph is preferred ...

Parsons

Software Developer - TS/SCI

Herndon, VA

Senior members at BRE also directly assist with winning new work, writing proposals, and ... CUDA/GPU, Grid Systems, Parallel Processing, Threading * An active TS/SCI w/polygraph is preferred ...

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Assistant Cuda information

What are the roles and responsibilities of an assistant CUDA developer?

An Assistant Cuda typically supports senior CUDA (Compute Unified Device Architecture) developers or teams working with NVIDIA’s parallel computing platform. Their responsibilities include assisting in developing, testing, and optimizing code written for GPUs to accelerate computing tasks, debugging CUDA applications, and maintaining documentation. They may also handle routine tasks such as performance benchmarking, code reviews, and collaborating with other team members to implement efficient GPU solutions. This role is crucial in organizations that rely on high-performance computing, scientific simulations, or AI workloads.

What skills and qualifications are needed to thrive as an assistant CUDA developer?

To thrive as an Assistant CUDA Developer, you need strong programming skills in C/C++, a solid understanding of parallel computing concepts, and familiarity with GPU architectures, often backed by a degree in computer science or a related field. Proficiency with CUDA development tools, debugging utilities, and version control systems like Git is typically required. Attention to detail, problem-solving abilities, and effective communication are crucial soft skills for collaborating with teams and optimizing code. These skills ensure efficient development of high-performance applications and successful integration of GPU acceleration into software solutions.

What are common challenges faced by assistant CUDA developers when optimizing code for GPU performance?

Assistant CUDA developers often encounter challenges such as managing memory efficiently between the host and device, ensuring proper kernel parallelization, and avoiding thread divergence. Balancing occupancy and resource usage can also be tricky, as it requires a deep understanding of how CUDA schedules and executes threads. Collaborating closely with data scientists and other engineers is essential to identify performance bottlenecks and implement effective optimizations.

What is the difference between Assistant Cuda vs Assistant Data Analyst?

AspectAssistant CudaAssistant Data Analyst
Required CredentialsTypically a relevant degree in computer science or related fieldOften a degree in data science, statistics, or related field
Work EnvironmentTech companies, software development teams, AI projectsBusiness, finance, marketing, or research departments
Employer & Industry UsageUsed in tech and AI industries for supporting CUDA programming tasksCommon in data-driven industries for data processing and analysis

Assistant Cuda and Assistant Data Analyst roles share some technical background but differ mainly in focus. Assistant Cuda primarily supports GPU programming and AI development, while Assistant Data Analyst focuses on data interpretation and reporting. Both roles require relevant technical skills and are found in industries leveraging data and technology, but their daily tasks and industry applications vary significantly.

What are popular job titles related to Assistant Cuda jobs in Reston, VA?

For Assistant Cuda jobs in Reston, VA, the most frequently searched job titles are:

What job categories do people searching Assistant Cuda jobs in Reston, VA look for?

The top searched job categories for Assistant Cuda jobs in Reston, VA are:

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Cities near Reston, VA with the most Assistant Cuda job openings:

Assistant Cuda jobs near you

Artificial Intelligence / Machine Learning Data Engineer

MAG Aerospace

Fairfax, VA • On-site

$116K - $140K/yr

Full-time

Re-posted 21 days ago

Job description

Position Summary
MAG Aerospace is staffing for a Artificial Intelligence / Machine Learning Data Engineer.
This position will lead the development of intelligent systems that transform multi-modal sensor data into actionable intelligence for tactical operations. You'll leverage COTS, FOSS/OSS, and custom development to build or integrate everything from edge computer vision to conversational AI assistants, while managing the data pipelines that feed these systems in the most challenging environments. While you'll have a core expertise in either data engineering or model development, you have a passion for mastering the full stack of AI systems.
US Citizens Only
Former US Defense Contractor / US Gov / US Military Experience Only
This is a Hybrid Position - Remote mainly - but as well on call to come into a MAG office when requested
We are seeking candidates who live in proximity to our corporate HQ in Fairfax, VA primarily but will entertain persons living near our satellite offices in:
Aberdeen, MD - Titusville, FL - Newport News, VA - Carthage NC
Essential Duties and Responsibilities
Duties include, but not limited to:
Primary Responsibilities:
  • Develop and optimize data-centric AI solutions such as computer vision pipelines for object detection, tracking, and classification
  • Implement advanced AI capabilities including RAG systems, agentic workflows, and fine-tuned LLMs
  • Design and deploy edge-optimized models using TensorRT, ONNX, and quantization techniques
  • Build data engineering pipelines for ETL, feature engineering, and model training
  • Create analytics dashboards and business intelligence solutions for operational insights
  • Implement multi-modal sensor fusion algorithms (visual, thermal, acoustic, RF)
  • Design and maintain data lakes, warehouses, and real-time streaming architectures
  • Develop conversational AI interfaces using open-source LLMs (Llama, Mistral, etc.)
  • Establish and enforce data quality standards, validation checks, and governance procedures throughout the data lifecycle
  • Develop and implement robust testing and validation strategies for AI/ML models, including performance under degraded data conditions, adversarial testing, and operational scenarios
Secondary Responsibilities:
  • Optimize AI workloads for embedded platforms (Jetson, Intel Neural Compute Stick)
  • Implement hardware acceleration using CUDA and TensorRT
  • Profile and optimize memory/power consumption for edge devices
  • Support embedded systems team with AI-specific hardware integration
  • Design distributed inference systems for degraded network conditions

Requirements
Minimum Requirements:
Primary Experience / Qualifications:
  • 5+ years' experience in machine learning, AI, and data engineering
  • Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow, JAX)
  • Experience with modern AI paradigms (transformers, diffusion models, neural ODEs)
  • Hands-on experience with LLM deployment and optimization (vLLM, TGI, llama.cpp)
  • Proficiency with data engineering tools (Apache Spark, Airflow, dbt, etc.)
  • Experience with both SQL and NoSQL databases at scale
  • Knowledge of vector databases and embedding systems (Pinecone, Weaviate, pgvector)
  • Experience with computer vision libraries (OpenCV, PIL) and video processing
  • Understanding of MLOps practices and model lifecycle management
Preferred Qualifications
  • Experience with military/defense AI applications
  • Knowledge of agentic AI frameworks (LangChain, AutoGPT, CrewAI)
  • Familiarity with federated learning and edge-cloud hybrid architectures
  • Experience with business intelligence tools (Tableau, PowerBI, Grafana)
  • Knowledge of time-series analysis and anomaly detection
  • Experience with knowledge graphs and semantic reasoning
  • Understanding of explainable AI and model interpretability
  • Experience with MLOps platforms and tools (e.g., MLflow, Kubeflow, Weights & Biases)
  • Published research or patents in relevant areas

Education & Experience:
  • Bachelor's degree in CS, EE, or related field;
  • Master's preferred

Clearance:
  • Must be eligible for Secret security clearance

Other Qualifications:
  • Must be a US citizen

Special Note
What Makes You Successful Here
  • You can build anything from a computer vision pipeline to a conversational AI assistant
  • You treat data engineering as seriously as model development
  • You understand the tradeoffs between cloud-scale and edge deployment
  • You can explain complex AI concepts to operators and executives alike
  • You see AI as a tool for augmenting human decision-making, not replacing it

Why Join MAG:
  • Work on meaningful problems that directly impact national security
  • Small, elite team where your contributions matter immediately
  • Access to cutting-edge hardware and technologies
  • Rapid prototyping environment - see your ideas deployed in weeks
  • Direct interaction with end users and field deployments
  • Professional development and conference attendance support
  • Flexible work arrangements with occasional field exercises
  • Opportunity to shape the future of tactical edge computing

Company Policy
MAG Aerospace (MAG) is an Equal Opportunity/Affirmative Action Employer and is committed to Diversity and Inclusion. We encourage diverse candidates to apply to our positions.
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status.
Click below for the "EEO is The Law" and "Pay Transparency Nondiscrimination" supplement posters.
https://www.dol.gov/agencies/ofccp/posters
MAG Aerospace (MAG) is committed to providing an online application process that is accessible to all, including individuals with a disability, by offering an alternative way to apply for job openings. This alternative method is available for those who cannot otherwise complete the online application due to a disability or need for accommodation.
MAG provides reasonable accommodation to applicants under the guidance of the Americans with Disabilities Act (ADA), Section 503 of the Rehabilitation Act of 1973, the Vietnam-Era Veterans' Readjustment Assistance Act of 1974, and certain state and/or local laws.
If you need assistance due to a disability, please contact the MAG Aerospace Recruiting email:
Applicant.Assist@magaero.com or call (703) 376-8993.

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