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Assistant Cuda Jobs in Springfield, VA (NOW HIRING)

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

Software Developer - TS/SCI

Chantilly, 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 ...

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

Herndon, 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

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 ...

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Assistant Cuda information

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 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 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 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.
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What job categories do people searching Assistant Cuda jobs in Springfield, VA look for? The top searched job categories for Assistant Cuda jobs in Springfield, VA are:
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Assistant Cuda jobs near you

Senior Engineer, State Estimation (R5165)

Shield AI

Washington, DC • On-site

$160K - $240K/yr

Full-time

Re-posted 27 days ago

Job description

Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI's technology actively supports operations worldwide. For more information, visit www.shield.ai. Follow Shield AI on LinkedIn, X, Instagram, and YouTube. 

Founded in 2015, Shield AI is a venture-backed defense technology company whose mission is to protect service members and civilians with intelligent systems. In pursuit of this mission, Shield AI is building the world's best AI pilot. Its AI pilot, Hivemind, has flown a fighter jet (F-16), a vertical takeoff and landing drone (X-BAT), and a quadcopter (Nova). The company has offices in San Diego, Dallas, Washington DC and abroad. Shield AI's products and people are currently in the field actively supporting operations with the U.S. Department of Defense and U.S. allies.  As a State Estimation Engineer, you will work on the GNC team to develop and optimize algorithms that process and fuse data from various sensors to provide accurate, reliable state estimates, enabling the X-BAT to operate autonomously in complex and contested environments. 
WHAT YOU'LL DO:
  • Develop and implement advanced sensor algorithms for processing data from IMUs, radar, cameras, GPS, and other sensors.  
  • Enhance state estimation algorithms by integrating multi-sensor data for improved accuracy and robustness. 
  • Design and implement real-time sensor data processing pipelines. 
  • Collaborate with cross-functional teams, including software engineers, autonomy researchers, and hardware engineers, to ensure seamless integration of state estimation algorithms.  
  • Conduct experiments and field tests to validate the performance of state estimation algorithms in real-world scenarios.  
  • Stay updated with the latest advancements in sensor technologies and state estimation , applying them to our systems.
REQUIRED QUALIFICATIONS:
  • Typically requires a minimum of 5 years of related experience with a Bachelor's degree; or 4 years and a Master's degree; or 2 years with a PhD; or equivalent work experience.
  • Experience developing and deploying real-time sensor processing algorithms, e.g. with cameras, radar, IMUs, GPS, etc.  
  • Solid understanding of state estimation techniques, such as Kalman filters, particle filters, etc.  
  • Experience with C++ 11 or newer  
  • Experience with Linux, command line tools, etc.  
  • Excellent communication skills, with the ability to effectively collaborate with multidisciplinary teams and external stakeholders.  
  • Proven track record of successfully shipping products, showcasing the ability to navigate through development cycles, overcome obstacles, and deliver high-quality solutions to meet project deadlines and exceed expectations in a fast-paced environment.  
  • You have a demonstrated record of working hard, being a trustworthy teammate, holding yourself and others to high standards, and being kind to others.
  • Ability to obtain a S//SAR level security clearance desired.
PREFERRED QUALIFICATIONS:
  • Experience in implementing inertial navigation algorithms on real-time processing systems  
  • Knowledge of computer vision techniques  
  • Proficiency in optimizing algorithms for compute-constrained systems  
  • Experience with CUDA or other hardware acceleration technologies (e.g. FPGAs)  
  • Proven track record of transitioning from R&D to production
$160,000 - $240,000 a year
Full-time regular employee offer package:
Pay within range listed + Bonus + Benefits + Equity
 
Temporary employee offer package:
Pay within range listed above + temporary benefits package (applicable after 60 days of employment)
 
Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information.
 
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Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know. 
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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