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Remote Memory Design Engineer Jobs in Georgia (NOW HIRING)

PRAGMATIKE

CUDA Kernel Engineer

Atlanta, GA · Remote

Remote US Start date: ASAP Languages: English (required) About the Role Pragmatike is hiring on ... Strong ability to optimize kernels (tiling strategies, occupancy tuning, shared memory design, warp ...

HBK Engineering, LLC

Design Technician

Atlanta, GA · On-site +1

About Us HBK Engineering, LLC is a fully licensed, professional engineering design firm ... Understanding of remote communication software. * Ability to come up to speed quickly on in-process ...

Aflac Incorporated

Software Engineer III

Columbus, GA · On-site +1

$96.96K - $140K/yr

If the role is remote, there may be occasions that you are requested to come to the office based on ... Database, SQL, and API Integration Design and implement database interactions using SQL with JDBC ...

Aflac

Software Engineer III

Columbus, GA · On-site +1

$96.96K - $140K/yr

If the role is remote, there may be occasions that you are requested to come to the office based on ... memory leaks and optimize heap usage. Efficiently handle paginated collections and apply best ...

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Remote Memory Design Engineer information

What are the key skills and qualifications needed to thrive as a Remote Memory Design Engineer, and why are they important?

To thrive as a Remote Memory Design Engineer, you need a solid understanding of digital circuit design, semiconductor memory architecture, and a degree in electrical or computer engineering. Familiarity with EDA tools like Cadence and Synopsys, as well as experience with hardware description languages such as Verilog or VHDL, are typically required. Strong problem-solving abilities, attention to detail, and effective remote communication skills set outstanding candidates apart. These skills ensure the ability to design reliable, high-performance memory circuits while collaborating efficiently with distributed teams.

What are some common challenges faced by remote memory design engineers, and how can they be addressed?

Remote memory design engineers often encounter challenges such as collaborating effectively with globally distributed teams, managing complex hardware-software integration remotely, and ensuring clear communication on intricate design specifications. These obstacles can be addressed by leveraging collaborative design tools, participating in regular virtual meetings, and maintaining thorough documentation to align with team members. Proactive communication and strong organizational skills are crucial for staying synchronized with project milestones and quickly resolving technical issues.

What does a Remote Memory Design Engineer do?

A Remote Memory Design Engineer is responsible for designing and developing memory components, such as DRAM, SRAM, or Flash, used in electronic devices and systems. Working remotely, they collaborate with hardware and software teams to optimize memory performance, power consumption, and reliability. Their work often includes circuit design, simulation, validation, and troubleshooting. They also stay updated on the latest memory technologies and may contribute to documentation and technical support.

What is the difference between Remote Memory Design Engineer vs Memory Architect?

AspectRemote Memory Design EngineerMemory Architect
CredentialsBachelor's or Master's in Electrical Engineering or Computer EngineeringBachelor's or Master's in Electrical Engineering, Computer Engineering, or related fields; often with specialized certifications
Work EnvironmentDesign teams, R&D labs, semiconductor companies, often collaborative and project-basedHigh-level planning, system-level design, often in R&D or architecture teams
Industry UsageUsed in semiconductor, electronics, and hardware development companiesPrimarily in chip design, hardware architecture firms, and large tech companies

The Remote Memory Design Engineer focuses on designing and optimizing memory components at the circuit level, while the Memory Architect develops overall memory system architectures and strategies. Both roles require strong technical skills, but the Design Engineer is more hands-on with hardware implementation, whereas the Architect works on high-level design and system integration.

What are the most commonly searched types of Memory Design Engineer jobs in Georgia? The most popular types of Memory Design Engineer jobs in Georgia are:
What are popular job titles related to Remote Memory Design Engineer jobs in Georgia? For Remote Memory Design Engineer jobs in Georgia, the most frequently searched job titles are:
What job categories do people searching Remote Memory Design Engineer jobs in Georgia look for? The top searched job categories for Remote Memory Design Engineer jobs in Georgia are:
What cities in Georgia are hiring for Remote Memory Design Engineer jobs? Cities in Georgia with the most Remote Memory Design Engineer job openings:
Remote Memory Design Engineer jobs near you

CUDA Kernel Engineer

PRAGMATIKE

Atlanta, GA • Remote

Full-time

Medical, Dental, Vision, Retirement

Posted 25 days ago

Job description

Location: Remote US
Start date: ASAP
Languages: English (required)

About the Role

Pragmatike is hiring on behalf of a fast-growing AI startup recognized as a Top 10 GenAI company by GTM Capital, founded by MIT CSAIL researchers.

We are searching for a CUDA Kernel Engineer who has hands-on experience developing and optimizing NVIDIA CUDA kernels from scratch. You will work on the GPU performance layer powering large-scale, high-throughput AI systems used by Fortune 500 customers.

This role is ideal for someone who deeply understands NVIDIA GPU architecture, memory hierarchy, warp-level execution, and profiling workflowsnot someone coming from generic hardware, FPGA, or non-NVIDIA compute backgrounds. You will directly influence the GPU efficiency, throughput, and scalability of mission-critical AI systems.

What Youll Do

  • Design, implement, and optimize custom CUDA kernels for NVIDIA GPUs, with a focus on maximizing occupancy, memory throughput, and warp efficiency.
  • Profile GPU workloads using tools such as Nsight Compute, Nsight Systems, nvprof, and CUDA‐MEMCHECK.
  • Analyze and eliminate performance bottlenecks including warp divergence, uncoalesced memory access, register pressure, and PCIe transfer overhead.
  • Improve GPU memory pipelines (global, shared, L2, texture memory) and ensure proper memory coalescing.
  • Collaborate closely with AI systems, model acceleration, and backend distributed systems teams.
  • Contribute to GPU architecture decisions, kernel libraries, and internal performance-engineering best practices.

What Were Looking For

  • Proven track record building NVIDIA CUDA kernels from scratchnot just calling existing libraries.
  • Strong ability to optimize kernels (tiling strategies, occupancy tuning, shared memory design, warp scheduling).
  • Deep understanding of CUDA threads, warps, blocks, and grids, GPU memory hierarchy and memory coalescing, as well as warp divergence (how to detect, analyze, and mitigate it)
  • Experience diagnosing PCIe bottlenecks and optimizing host-device transfers (pinned memory, streams, batching, overlap).
  • Familiarity with C++, CUDA runtime APIs, and GPU debugging/profiling tooling.

Bonus Points

  • Experience with multi-GPU or distributed GPU systems (NCCL, NVLink, MIG).
  • Background in GPU acceleration for ML frameworks or HPC workloads.
  • Knowledge of model inference optimization (TensorRT, CUDA Graphs, CUTLASS).
  • Exposure to compiler-level optimization or PTX/SASS analysis.
  • Startup experience or comfort working in fast-moving, ambiguous environments.

Why This Role Will Pivot Your Career

  • Research pedigree: MIT CSAIL founders recognized for breakthrough AI and systems contributions.
  • Customer impact: Deploy AI solutions powering Fortune 500 clients.
  • Industry momentum: Lab alumni have led high-value acquisitions (MosaicML Databricks, Run:AI Nvidia, W&B CoreWeave).
  • Funding & growth: Oversubscribed seed round, next funding in 2026.
  • Career growth & influence: Lead AI initiatives, optimize pipelines, and directly impact production AI systems at scale.
  • Culture & autonomy: Own critical systems while collaborating with world-class engineers.
  • Aspirational impact: Solve GPU/AI performance challenges few engineers ever face.

Benefits

  • Competitive salary & equity options
  • Sign-on bonus
  • Health, Dental, and Vision
  • 401k

Pragmatike is an Equal Opportunity Employer and is committed to providing equal employment opportunities to all applicants without discrimination. We recruit on behalf of our clients and prohibit discrimination and harassment based on race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.We are committed to a fair and inclusive hiring process. We process your personal data solely for recruitment purposes, in accordance with applicable privacy laws, and maintain reasonable safeguards to protect your information. Your data may be shared with our client(s) for hiring consideration, but will not be disclosed to third parties outside of the recruitment process.