Software Engineer Jobs in Santa Clara, CA

Lead architecture and implementation of hardware abstraction layers, drivers, runtimes, and data-movement pipelines in Rust. Drive platform bring-up, triage difficult runtime and hardware faults, define long-lived APIs and compatibility practices, establish AI-assisted engineering workflows, and collaborate with hardware, compiler, and operations teams to ensure production-scale reliability and performance.

Develop and maintain FortiClient Windows software using C/C++; design network and VPN features, implement Windows drivers, diagnose networking/security issues, collaborate with global teams, and contribute to product quality and innovation.

As a Senior Software Engineer, you'll design and implement scalable, low-latency software for GM's ADAS features, collaborating on complex systems and mentoring other developers.

Architect, implement, and optimize scalable hybrid (cloud and on‑prem) infrastructure. Lead automation, CI/CD, deployment, and IaC practices; mentor engineers; improve developer experience; collaborate with Solutions Architects, Field Engineers, and product teams to deliver integrated solutions.

Lead performance and scalability engineering for Kubernetes-based accelerated AI runtimes. Analyze end-to-end stack from orchestration to hardware, design upstream Kubernetes changes, improve container startup and encrypted inference performance, build large-scale simulations and automated workload tests, and engage upstream communities and customers to validate and ship scalable AI infrastructure.

Develop cloud infrastructure and DevOps software across the SDLC, implement features and tests, drive operational excellence, coordinate and lead engineering work, set engineering standards, improve processes, and represent PayPal with partners and customers.

Build and maintain containerized GPU-accelerated workloads, run and analyze large-scale benchmarking on HPC clusters, visualize performance data and dashboards, and collaborate on reference financial AI models and tooling to evaluate training, inference, and optimization performance.

Evaluate and optimize NVIDIA AI infrastructure by running multi-node training/inference on large GPU clusters, designing benchmarks, profiling deep-learning workloads, identifying bottlenecks, producing tutorials and whitepapers, analyzing competitors, and presenting demos at major conferences.

Develop and maintain infrastructure for software development and AI operations, manage CI/CD pipelines, and automate configurations using various tools.

Own and maintain a Yocto/OpenEmbedded-based embedded Linux distribution for a medical device laptop. Lead hardware bring-up, secure boot and TPM management, field update mechanisms, OS security hardening, platform debugging, platform services, and cross-functional documentation for regulated device development.

Build and maintain backend APIs and data pipelines that ingest and process large-scale construction data (360° video, schedules, IoT). Optimize storage and query performance using DuckDB and PostgreSQL, extend Airflow workflows, integrate Wasm for local computation, monitor data quality, and collaborate with frontend, CV, and ML teams to deploy production models and analytics.

Develop and optimize compiler, runtime, and SDK components for TetraMem's analog compute-in-memory AI hardware. Translate ML models into efficient executables, implement low-level optimizations and debugging tools, integrate ML frameworks and deployment pipelines, benchmark and profile workloads, support hardware bring-up and validation, and collaborate across teams to improve system performance.

As a Software Engineer focused on Data at Speechify, you'll manage data collection and ingestion for model training, enhance cloud infrastructure, and collaborate closely with AI scientists to optimize data quality and cost-efficiency for next-gen products.

The Senior iOS Engineer will lead engineering decisions, ship production code, maintain app architecture, and enhance user experiences for Speechify's iOS app.

As a Senior Software Engineer II, you'll design and operate a Kubernetes-native platform for AI workload orchestration, improve performance, and mentor engineers.

As a Senior Software Engineer on the Developer Experience team, you will drive architectural decisions, design systems for developer productivity, mentor engineers, and enhance the platform's capabilities to improve developer workflows and system reliability.

The Staff Software Engineer leads the Developer Experience team, driving technical strategies and addressing complex developer productivity challenges at CoreWeave, focusing on building robust developer platforms and enhancing engineering processes.

As a Senior Software Engineer on the Cash App Banking team, you will lead the design, execution, and delivery of banking features, collaborating across teams to enhance the user experience.

Lead design reviews and architecture in a Kubernetes-native inference platform, improve latency and reliability, mentor engineers, and implement optimizations.

The Staff Software Engineer will lead the architecture and design for AI workload orchestration on Kubernetes, mentoring engineers and driving technical initiatives across teams.

Engineer software that connects AI-driven platforms to datacenter power infrastructure. Develop control strategies and optimize energy use and AI workloads.

Responsible for architecting and developing AI security infrastructure, optimizing performance and scalability of systems, and driving innovation in a collaborative environment.

Design and implement high-performance datapath features (load balancing, firewall rules, L7 protocols) using deep C/C++ expertise. Drive projects end-to-end, optimize networking on Unix/Linux, and apply networking protocol knowledge (DNS, HTTP, TCP/IP, SSL/TLS).

The role involves developing software for optical test automation, managing data pipelines, collaborating across teams, and enhancing testing efficiency for silicon photonics.

The Software Engineer will develop new products and features for autonomy workflows, collaborate with experts, and take ownership of technical decisions.