Top Remote C++ Jobs in San Diego, CA

Design and optimize high-performance C++/CUDA libraries for GPU-based data processing. Improve multi-node GPU communication (UcxExchange), optimize Presto GPU query performance, and lead enhancements across Presto, Velox, and cuDF projects for efficient DataFrame and database acceleration.

Lead architecture and technical direction for Ocient's Loading and Transformation platforms, designing scalable batch and stream ingestion systems. Own ambiguous, cross-team initiatives end-to-end, mentor engineers, and implement high-performance distributed software using modern C++ and/or Java. Partner with product, sales, and customers to translate needs into reliable, petabyte-scale solutions.

Lead engineering of core scheduling and orchestration subsystems for an orbital edge compute platform. Own an MVP for autonomous scheduling across compute node fleets, scale to larger satellite fleets with data sovereignty, design performant and reliable distributed engines, build scheduling and workload-placement logic for intermittent-connectivity edge environments, and provide technical leadership while partnering with cross-functional teams to deliver secure, customer-focused solutions.

Analyze and optimize HPC application performance across CPU and multi-node multi-GPU systems by driving compiler and library improvements. Port and tune applications, evaluate compiler/runtime/driver impacts, and collaborate with compiler development and application engineering teams to deliver performance enhancements.

Lead cross-stack adoption of modern toolchains, build and code-health practices, and performance workflows on NVIDIA CPU platforms. Integrate and validate compilers, linkers, cross-compilation, and CI; profile and optimize large codebases; build automation and playbooks; drive integration blockers to owners and communicate measurable before-and-after results to engineering teams and leadership.

Work as the US-based technical face for Bitmovin's Encoding team: contribute production C++/Java/Kotlin code, triage and resolve customer encoding incidents during US hours, run on-site integrations and workshops, and feed field learnings into sprint planning and the product roadmap.

Build and maintain the GG App across Windows, macOS, and iOS including installers, background services, auto-update systems, enterprise deployment paths, health reporting, AWS backend, and documentation. Lead architecture decisions, mentor engineers, participate in on-call support, and champion AI adoption and automation across engineering.

Lead design and delivery of cloud and AI production systems, partner with stakeholders to translate needs into architecture, ensure security and quality, mentor engineers, and drive customer adoption and scalable reusable solutions across engagements.

Build, integrate, and stress-test full-stack applications and backend services that leverage advanced AI models. Develop production APIs, front-end features, databases, and cloud infrastructure; troubleshoot integrations; prototype rapidly and deliver high-quality code and documentation in fast-moving environments.

Design and scale high-performance Ethernet and InfiniBand fabrics for hyperscale AI training clusters. Develop ROCE transport and congestion-control mechanisms, topology and routing strategies, telemetry and observability, cluster bring-up, benchmarking, tuning, and cross-vendor co-design to enable low-latency, lossless networks at 10k–100k+ GPU scale.

Lead development of core client systems and engine-level infrastructure in Unity/C#. Diagnose and fix cross-cutting performance issues, upgrade third-party SDKs, evolve build tooling, produce design docs, scope multi-week infrastructure initiatives, mentor engineers, and drive profiling, optimization, and architecture changes to enable future features.

Design, develop, and maintain manufacturing and production test software for programming, calibrating, and verifying products. Integrate with embedded systems and test instruments, implement automated test sequences and traceability, investigate failures, and improve throughput, quality, and yield across factory programming stations and production fixtures.

Contract GPU kernel optimization role: analyze profiler metrics, identify bottlenecks, and improve kernel performance across modern GPU hardware. Implement and modify C++17, Python, and GPU code using CUDA/HIP/shaders, document optimization decisions, and collaborate as a freelance specialist (20+ hrs/week preferred).

Participate in full SDLC building and integrating software for DoD customers. Develop C++/Python systems, curate synthetic geospatial raster data, apply TDD, operate in DevSecOps pipelines, and use containerization and CI/CD for deployment and testing.

Define and execute verification plans for block-to-full-chip ASICs using SystemVerilog/UVM. Build testbenches, assertions, constrained-random and directed tests, manage regressions and CI, run simulations, triage failures, close coverage, and support silicon bring-up and post-silicon debug while collaborating across architecture, RTL, DFT, firmware, and physical design teams.

As a Windows Engineer at Upwind, you will develop security modules, lead projects from inception to production, and collaborate across teams.

The role involves modeling and verifying analog/mixed-signal IPs, collaborating with teams for optimal performance in communication SoCs.

Develop and optimize CUDA kernels and GPU-accelerated software for latency-sensitive, high-throughput workloads. Profile and tune GPU performance, scale multi-GPU/multi-node systems, build tooling to correlate GPU utilization with real-time energy/grid signals, collaborate with infrastructure and ML teams, and contribute to libraries and best practices for GPU performance in data center environments.

The role involves designing and optimizing GPU architectures for AI Inference, analyzing hardware-software relationships, and developing performance models.

Develop innovative physical design methodologies for GPUs and SOCs, focusing on PPA improvements and collaboration across multiple teams. Use AI/ML to enhance design efficiency.

Design and maintain system software for GPU communication, develop architectural solutions for computing platforms, and work with cross-disciplinary teams.

As a Principal Software Engineer, you will architect AI-enabled systems, mentor teams, and guide technical decisions for scalable products.

Migrate and operate customer experience applications on Google Cloud. Perform lift-and-shift to GCP, deploy and validate releases, manage containerized microservices (GKE/Docker/Terraform), query and configure apps, use Jenkins/git for pre-staging, and troubleshoot Linux/Unix systems with scripting.

Design and implement an LLVM-based backend JIT compiler for NVIDIA GPUs. Develop compiler passes and optimizations, focusing on high performance and low compile time. Collaborate with hardware, compiler, and application teams to resolve issues and influence future GPU architectures.

Lead development and adoption of Warp by implementing CUDA C++ and Python integrations, turning CUDA features into supported functionality, integrating CUDA-X libraries, partnering with internal teams for production integration, and designing APIs and abstractions to expand simulation, optimization, and AI workloads.