Performance Engineer
Palo Alto, CA · On-site
... high-performance computing • Familiarity with profiling tools, performance debugging, tracing ... both engineers and customers Preferred : • Experience with CUDA, Triton, Pallas, ROCm, XLA, or ...
Performance Engineer
Palo Alto, CA · On-site
... high-performance computing • Familiarity with profiling tools, performance debugging, tracing ... both engineers and customers Preferred : • Experience with CUDA, Triton, Pallas, ROCm, XLA, or ...
... high-performance computing. * Hands-on experience with LLMs, multimodal models, or transformer ... Experience with GPU or accelerator programming using CUDA, Triton, OpenCL, or similar technologies.
... high-performance computing. * Hands-on experience with LLMs, multimodal models, or transformer ... Experience with GPU or accelerator programming using CUDA, Triton, OpenCL, or similar technologies.
... and high-performance computing applications. The Senior Kernel Performance Architect for Deep ... Required : • A Master's or PhD in Computer Science, Electrical Engineering or Computer ...
... and high-performance computing applications. The Senior Kernel Performance Architect for Deep ... Required : • A Master's or PhD in Computer Science, Electrical Engineering or Computer ...
Performance Engineer
Palo Alto, CA · On-site
... high-performance computing • Familiarity with profiling tools, performance debugging, tracing ... both engineers and customers Preferred : • Experience with CUDA, Triton, Pallas, ROCm, XLA, or ...
Performance Engineer
Palo Alto, CA · On-site
... high-performance computing • Familiarity with profiling tools, performance debugging, tracing ... both engineers and customers Preferred : • Experience with CUDA, Triton, Pallas, ROCm, XLA, or ...
... high-performance computing, and distributed architectures. You will architect and implement ... Key job responsibilities Our kernel engineers collaborate across compiler, runtime, framework, and ...
... high-performance computing, and distributed architectures. You will architect and implement ... Key job responsibilities Our kernel engineers collaborate across compiler, runtime, framework, and ...
You would work directly with the engineer who architected the fault-tolerant computing and ... Modern, high-performance compute platforms , not legacy aerospace hardware * Real authority over ...
Quick apply
You would work directly with the engineer who architected the fault-tolerant computing and ... Modern, high-performance compute platforms , not legacy aerospace hardware * Real authority over ...
... learning, high-performance computing, and distributed architectures You will architect and ... Key job responsibilities Our kernel engineers collaborate across compiler, runtime, framework, and ...
... learning, high-performance computing, and distributed architectures You will architect and ... Key job responsibilities Our kernel engineers collaborate across compiler, runtime, framework, and ...
... learning, high-performance computing, and distributed architectures You will architect and ... Key job responsibilities Our kernel engineers collaborate across compiler, runtime, framework, and ...
... learning, high-performance computing, and distributed architectures You will architect and ... Key job responsibilities Our kernel engineers collaborate across compiler, runtime, framework, and ...
Research Computing Cloud Engineer
Stanford, CA · On-site
$65.50 - $87.75/hr
... projects, including high-performance computing and AI/ML workloads. Responsibilities : • ... Preferred : • Degree in Computer Science, Engineering, or equivalent professional experience in a ...
Research Computing Cloud Engineer
Stanford, CA · On-site
$65.50 - $87.75/hr
... projects, including high-performance computing and AI/ML workloads. Responsibilities : • ... Preferred : • Degree in Computer Science, Engineering, or equivalent professional experience in a ...
Research Software Engineer I - Center for AI and Research Computing (AIRC)
La Jolla, CA · On-site
$217K/yr
Support the administration, configuration, and integration of high-performance computing (HPC ... Write well-documented, tested code and follow professional software engineering practices ...
Research Software Engineer I - Center for AI and Research Computing (AIRC)
La Jolla, CA · On-site
$217K/yr
Support the administration, configuration, and integration of high-performance computing (HPC ... Write well-documented, tested code and follow professional software engineering practices ...
Research Software Engineer I - Center for AI and Research Computing (AIRC)
La Jolla, CA · On-site
$214K/yr
Support the administration, configuration, and integration of high-performance computing (HPC ... Write well-documented, tested code and follow professional software engineering practices ...
Research Software Engineer I - Center for AI and Research Computing (AIRC)
La Jolla, CA · On-site
$214K/yr
Support the administration, configuration, and integration of high-performance computing (HPC ... Write well-documented, tested code and follow professional software engineering practices ...
NVIDIA has been transforming computer graphics and accelerated computing for over 25 years. They are looking for senior engineers obsessed with performance analysis and optimization to enhance AI ...
NVIDIA has been transforming computer graphics and accelerated computing for over 25 years. They are looking for senior engineers obsessed with performance analysis and optimization to enhance AI ...
We are now looking for a Senior High-Performance LLM Training Engineer! NVIDIA is seeking ... GPU computing is the most productive and pervasive platform for deep learning and AI. It begins ...
We are now looking for a Senior High-Performance LLM Training Engineer! NVIDIA is seeking ... GPU computing is the most productive and pervasive platform for deep learning and AI. It begins ...
We are now looking for a Senior High-Performance LLM Training Engineer! NVIDIA is seeking ... GPU computing is the most productive and pervasive platform for deep learning and AI. It begins ...
We are now looking for a Senior High-Performance LLM Training Engineer! NVIDIA is seeking ... GPU computing is the most productive and pervasive platform for deep learning and AI. It begins ...
NVIDIA is seeking a Principal Engineer to drive the performance of large-scale AI training and post ... NVIDIA is a computing platform company operating at the intersection of graphics, HPC, and AI.
NVIDIA is seeking a Principal Engineer to drive the performance of large-scale AI training and post ... NVIDIA is a computing platform company operating at the intersection of graphics, HPC, and AI.
Software Engineering Manager, ML Kernel Performance, AWS Neuron, Annapurna Labs
Cupertino, CA · On-site
$172K/yr
... high-performance computing, and distributed architectures. You will architect and implement ... Key job responsibilities Our kernel engineers collaborate across compiler, runtime, framework, and ...
Software Engineering Manager, ML Kernel Performance, AWS Neuron, Annapurna Labs
Cupertino, CA · On-site
$172K/yr
... high-performance computing, and distributed architectures. You will architect and implement ... Key job responsibilities Our kernel engineers collaborate across compiler, runtime, framework, and ...
System Performance Modeling Engineer
Santa Clara, CA · On-site
$165K/yr
In this role, you will work on advanced ASIC and SoC platforms that power high-performance computing and data center solutions. As a Senior Modeling Engineer, you will collaborate closely with ...
System Performance Modeling Engineer
Santa Clara, CA · On-site
$165K/yr
In this role, you will work on advanced ASIC and SoC platforms that power high-performance computing and data center solutions. As a Senior Modeling Engineer, you will collaborate closely with ...
Software Engineering Manager, ML Kernel Performance, AWS Neuron, Annapurna Labs
Cupertino, CA · On-site
$172K/yr
... learning, high-performance computing, and distributed architectures You will architect and ... Key job responsibilities Our kernel engineers collaborate across compiler, runtime, framework, and ...
Software Engineering Manager, ML Kernel Performance, AWS Neuron, Annapurna Labs
Cupertino, CA · On-site
$172K/yr
... learning, high-performance computing, and distributed architectures You will architect and ... Key job responsibilities Our kernel engineers collaborate across compiler, runtime, framework, and ...
... learning, high-performance computing, and distributed architectures You will architect and ... Key job responsibilities Our kernel engineers collaborate across compiler, runtime, framework, and ...
... learning, high-performance computing, and distributed architectures You will architect and ... Key job responsibilities Our kernel engineers collaborate across compiler, runtime, framework, and ...
System Performance Modeling Engineer
Santa Clara, CA · Hybrid
$118K - $161K/yr
In this role, you will work on advanced ASIC and SoC platforms that power high-performance computing and data center solutions. As a Senior Modeling Engineer, you will collaborate closely with ...
System Performance Modeling Engineer
Santa Clara, CA · Hybrid
$118K - $161K/yr
In this role, you will work on advanced ASIC and SoC platforms that power high-performance computing and data center solutions. As a Senior Modeling Engineer, you will collaborate closely with ...
Freelance High Performance Computing Engineer information
How do freelance High Performance Computing (HPC) Engineers typically collaborate with client teams during projects?
Freelance HPC Engineers often work closely with client engineering, research, or IT teams to design, implement, and optimize computational solutions. Collaboration usually occurs through regular virtual meetings, code reviews, and progress updates to ensure alignment with project goals and technical requirements. Clear communication and documentation are essential, as freelancers may need to integrate their work into larger systems or hand off projects to in-house teams. Building strong relationships and understanding the client's workflow help ensure successful project delivery and can lead to ongoing opportunities.
What is a Freelance High Performance Computing Engineer?
A Freelance High Performance Computing (HPC) Engineer is a professional who specializes in designing, implementing, and optimizing computing systems that handle complex, large-scale computations. They work independently or on a contract basis for different organizations, helping to develop and maintain supercomputers, clusters, and parallel processing applications. Their expertise is often sought in fields like scientific research, finance, artificial intelligence, and engineering where processing large datasets quickly is essential. Freelancers in this field typically possess strong programming skills, knowledge of HPC architectures, and experience with performance tuning and troubleshooting.
What are the key skills and qualifications needed to thrive as a Freelance High Performance Computing Engineer, and why are they important?
To thrive as a Freelance High Performance Computing Engineer, you need expertise in parallel programming, cluster management, and a strong background in computer science or engineering. Familiarity with tools such as MPI, OpenMP, Linux environments, and cloud-based HPC platforms, along with certifications in cloud services or HPC technologies, is highly beneficial. Excellent problem-solving, project management, and communication skills set top freelancers apart when working with diverse clients. These competencies ensure the delivery of optimized, scalable solutions and effective collaboration in complex technical projects.
What is the difference between Freelance High Performance Computing Engineer vs Freelance Data Scientist?
| Aspect | Freelance High Performance Computing Engineer | Freelance Data Scientist |
|---|---|---|
| Credentials | Advanced degrees in computer science, engineering, or related fields; knowledge of HPC systems | Degree in data science, statistics, or related fields; proficiency in programming and analytics |
| Work Environment | Specialized computing clusters, research labs, or cloud HPC platforms | Data analysis environments, cloud platforms, and business analytics tools |
| Industry Usage | Research institutions, scientific computing, engineering simulations | |
| Search & Comparison Intent | Focus on high-performance computing tasks, technical skills |
While both roles involve advanced technical skills, Freelance High Performance Computing Engineers specialize in optimizing and managing large-scale computing resources for scientific and engineering applications. Freelance Data Scientists focus on analyzing data to extract insights for business or research purposes. The key difference lies in their core focus: HPC engineers work with hardware and system performance, whereas data scientists work with data analysis and modeling.
What are the most commonly searched types of High Performance Computing Engineer jobs in California? The most popular types of High Performance Computing Engineer jobs in California are:
What are popular job titles related to Freelance High Performance Computing Engineer jobs in California? For Freelance High Performance Computing Engineer jobs in California, the most frequently searched job titles are:
What job categories do people searching Freelance High Performance Computing Engineer jobs in California look for? The top searched job categories for Freelance High Performance Computing Engineer jobs in California are:
What cities in California are hiring for Freelance High Performance Computing Engineer jobs? Cities in California with the most Freelance High Performance Computing Engineer job openings:
Full-time
Posted 9 days ago
Job description
Job Summary:
RadixArk is an infrastructure-first company focused on building world-class open systems for inference and training in AI. The Performance Engineer will analyze and improve performance across various production deployments and benchmark LLM inference and training workloads, ensuring optimal operation of AI systems in real environments.
Responsibilities:
• Analyze and improve performance across SGLang, Miles, and RadixArk production deployments
• Benchmark LLM inference and training workloads across GPUs, TPUs, and cloud environments
• Optimize latency, throughput, memory usage, batching, scheduling, routing, and GPU utilization
• Investigate performance regressions in real customer environments
• Work closely with kernel, runtime, distributed systems, and product engineers
• Build internal tooling for profiling, tracing, benchmarking, and regression detection
• Translate customer workload characteristics into concrete performance tuning strategies
• Help define performance metrics that matter commercially, including cost-per-token and serving efficiency
• Partner with customers and cloud partners on deep technical evaluations
• Contribute performance insights back to open-source SGLang and Miles
Qualifications:
Required:
• Strong systems engineering background, especially in performance-critical software
• Experience with GPU systems, distributed systems, inference serving, ML runtimes, or high-performance computing
• Familiarity with profiling tools, performance debugging, tracing, and benchmark methodology
• Comfort working with Python and C++
• Ability to debug messy real-world performance issues across software, hardware, and infrastructure layers
• Strong communication skills — you should be able to explain performance tradeoffs to both engineers and customers
Preferred:
• Experience with CUDA, Triton, Pallas, ROCm, XLA, or kernel-level optimization is a strong plus
• Understanding of LLM inference concepts such as batching, KV cache, prefill/decode, speculative decoding, MoE, long context, and P99 latency
• Prior experience with production AI infrastructure, cloud GPU environments, or open-source ML systems is a plus
Company:
RadixArk focuses on developing infrastructure for AI inference and training systems. Founded in 2025, the company is headquartered in San Francisco, USA, with a team of 11-50 employees. The company is currently Early Stage.
RadixArk is an infrastructure-first company focused on building world-class open systems for inference and training in AI. The Performance Engineer will analyze and improve performance across various production deployments and benchmark LLM inference and training workloads, ensuring optimal operation of AI systems in real environments.
Responsibilities:
• Analyze and improve performance across SGLang, Miles, and RadixArk production deployments
• Benchmark LLM inference and training workloads across GPUs, TPUs, and cloud environments
• Optimize latency, throughput, memory usage, batching, scheduling, routing, and GPU utilization
• Investigate performance regressions in real customer environments
• Work closely with kernel, runtime, distributed systems, and product engineers
• Build internal tooling for profiling, tracing, benchmarking, and regression detection
• Translate customer workload characteristics into concrete performance tuning strategies
• Help define performance metrics that matter commercially, including cost-per-token and serving efficiency
• Partner with customers and cloud partners on deep technical evaluations
• Contribute performance insights back to open-source SGLang and Miles
Qualifications:
Required:
• Strong systems engineering background, especially in performance-critical software
• Experience with GPU systems, distributed systems, inference serving, ML runtimes, or high-performance computing
• Familiarity with profiling tools, performance debugging, tracing, and benchmark methodology
• Comfort working with Python and C++
• Ability to debug messy real-world performance issues across software, hardware, and infrastructure layers
• Strong communication skills — you should be able to explain performance tradeoffs to both engineers and customers
Preferred:
• Experience with CUDA, Triton, Pallas, ROCm, XLA, or kernel-level optimization is a strong plus
• Understanding of LLM inference concepts such as batching, KV cache, prefill/decode, speculative decoding, MoE, long context, and P99 latency
• Prior experience with production AI infrastructure, cloud GPU environments, or open-source ML systems is a plus
Company:
RadixArk focuses on developing infrastructure for AI inference and training systems. Founded in 2025, the company is headquartered in San Francisco, USA, with a team of 11-50 employees. The company is currently Early Stage.