Software Engineer Jobs in Visalia, CA

Lead architecture and delivery of enterprise AI data platform transformations. Design and implement scalable lakehouse, streaming, and real-time analytics solutions. Lead migrations from Databricks/Snowflake/Azure/AWS to Oracle AI Data Platform, optimize Spark workloads, build reusable accelerators, drive AI/ML data pipelines and governance, advise executives, influence product roadmap, and mentor senior engineers globally.

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.

Design, develop, and operate large-scale SDN control and data plane software (OVS/OVN/OpenFlow) for NVIDIA AI Cloud. Build network orchestration and IaC (gRPC/REST, Ansible, Terraform, ArgoCD/Flux), maintain CI/CD pipelines, implement observability/monitoring, drive upstream open-source contributions, and collaborate with SRE/DevOps to ensure production reliability and performance SLAs.

Design, build, and optimize GPU‑accelerated inference software and open‑source frameworks (vLLM, SGLang, FlashInfer). Improve performance and scale for LLMs and generative models across NVIDIA GPUs and edge SoCs using CUDA, CUTLASS, Triton, NCCL and profiling tools. Collaborate across teams to enable efficient model serving and deployment.

Lead and execute perception R&D and engineering for factory robots: define multi-year roadmap, architect perception pipelines (detection, segmentation, 6-DoF pose, scene understanding), drive sensor fusion and calibration, establish data/model workflows and deployment practices, integrate with planning/control, hire and mentor engineers, and evaluate research for production adoption.

As a Senior Full Stack Software Engineer at Doxel, you will design and develop applications for project management, focusing on complex data handling and intuitive UI. Your role involves collaborating across teams and providing technical leadership in software projects.

Design and operate large-scale infrastructure supporting GPU- and CPU-based EDA workloads. Build automation for provisioning, configuration, deployment, lifecycle management, monitoring, health remediation, cluster enrollment, and recovery across Linux compute fleets. Integrate services with schedulers, infrastructure systems, and observability platforms. Participate in incident response, root-cause analysis, capacity planning, and reliability improvements while collaborating with EDA, networking, storage, and hardware teams.

As a Full Stack Software Engineer at Doxel, you will design and develop full-stack applications, collaborating cross-functionally to optimize user experiences and facilitate data processing for construction projects.

Own frontend architecture for multi-tenant applications serving internal, customer, and partner audiences. Build React and TypeScript interfaces, shared component libraries, theming and branding systems, accessible user experiences, and integrations with governed APIs. Establish engineering standards, document technical decisions, navigate open architecture questions, and support workflows ranging from immediate interactions to longer approval processes involving sensitive or regulated data.

Design, develop, and optimize system software and firmware for SoC-based O-RAN infrastructure. Implement power-management policies (DVFS, clock/power gating, thermal control), analyze RU/DU workloads, build performance and power models, create measurement and test tooling, validate on simulation/emulation and silicon, and influence SoC and platform architectures for 5G/6G deployments.

Architect and build Tagup’s core platform for ingesting, processing, and acting on billions of physical-world data points. Develop high-performance REST APIs, microservices, scalable ETL pipelines, AI-agent data systems, and cloud infrastructure. Own architectural domains spanning API design, data modeling, deployment, monitoring, and automated CI/CD. Ensure high availability, mentor junior engineers, and establish strong engineering standards while collaborating with data scientists and defense-focused operators.

Design, develop, optimize, and debug ultra low-latency C++ streaming systems and media pipelines (WebRTC, GStreamer, RTP). Analyze performance across CPU, memory, networking, and scheduling. Integrate streaming software with platform services across Windows, Linux, QNX, and embedded platforms. Define KPIs for networking and streaming quality and troubleshoot across software, OS, platform, and hardware boundaries.

Deploys and validates complete AI infrastructure software stacks on multi-node GPU systems, then converts implementations into technical documentation, automation, demos, training, and reference architectures. Tests prerelease software, evaluates interoperability and operational resilience, supports partners and field teams, collaborates with engineering and open-source communities, and recommends product improvements based on customer feedback. The role presents solutions through briefings, workshops, webinars, events, and internal training, with some travel required.

Lead performance practices for large-scale AI systems, enhance datacenter products, and resolve complex performance issues through collaboration and technical expertise.

As an ML Engineer at Luma AI, you will design high-performance model serving pipelines, manage GPU resources, and optimize CI/CD for large-scale AI systems.

The ML Engineer will integrate model architectures, optimize deployment workflows, maintain CI/CD pipelines, and ensure reliability of inference services across large-scale systems.

The role involves using AI tools to rapidly develop software, working across product and engineering teams, and owning software projects end-to-end.

This role requires shaping technical direction, leveraging AI tools for production systems, and making crucial decisions to align product intent with engineering realities.

You will design and implement IAM systems, own authentication and authorization, and ensure secure-by-default principles across Hadrian's API platform.

As a Senior Software Engineer at Ayama, you will build and improve AI-based systems, design data pipelines, and develop full-stack product features. This role requires strong architectural judgment and hands-on experience with optimization problems and large-scale data processing.

Lead architecture and delivery of Dialpad's agentic AI platform, building scalable multi-agent orchestration, memory and retrieval systems, real-time voice reasoning, inference optimization, safety/observability, and production integrations while mentoring engineers and partnering with product and research.

Design and build RL post-training infrastructure for AI, optimizing training-inference-rollout on distributed systems while ensuring fault tolerance and scalability.

Serve as technical lead between NVIDIA and hyperscale CSPs on GPU firmware and system software. Drive firmware update orchestration, recovery procedures, multi-GPU coordination, telemetry/health monitoring, and incorporate CSP feedback into NVIDIAs roadmap to improve fleet-scale manageability and reliability.

Lead technical engagements with cloud service providers on rack-scale system software and firmware. Drive architecture alignment, integration readiness, error handling and recovery, health telemetry, firmware orchestration, and serviceability. Capture CSP feedback, influence NVIDIA system software design, improve tooling and tests, and mitigate execution risks through early collaboration.

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.