Software Engineer Jobs in Oakland, CA

The Senior Software Engineer will develop mission simulation infrastructure, integrating various systems and ensuring safety-critical features for autonomous firefighting operations.

The Software Engineer, Perception develops autonomous aircraft systems to detect and manage wildfires using real-time data processing and machine learning techniques.

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 and build features for the SFS banking platform, onboard Block products, build secure fault-tolerant systems handling sensitive financial data, ensure service reliability, remediate incidents, and create durable operational fixes.

The Staff Software Engineer will develop and execute technical strategies for Cash App Banking, lead architectural decisions, and mentor engineers, focusing on innovative financial solutions.

The role requires designing and developing web applications and backend systems, integrating LLMs, and ensuring quality software delivery.

The Software Engineer will develop backend systems for an AI Energy Agent, including data integration, microservices, and scalable architecture, focusing on performance and reliability.

The Founding Software Engineer will build and enhance crisis-intervention software, focusing on mobile and web applications for government welfare, ensuring compliance and integrating data securely. Responsibilities include feature development, security enhancements, and managing interns.

The Full-Stack Engineer will develop and maintain web applications, translating UI/UX designs into responsive apps, optimizing applications, and writing clean code.

Build, test, and maintain software across full-stack, backend, infrastructure, data pipelines, and ML infrastructure to support autonomous trucking. Develop web interfaces, backend services, APIs, and tooling; improve reliability, observability, CI/CD, and deployment; participate in code reviews, debugging, and cross-team collaboration while learning new technologies.

Design and implement real-time MAC data-plane software for high-throughput satellite links. Build packet-processing pipelines, queue and buffer management, retransmission and loss recovery, and integrate with PHY, modem, FPGA, DMA, and SoC hardware. Optimize for low latency and high throughput using zero-copy, scatter-gather, lock-free structures, and hardware offload. Lead architecture through prototyping, hardware integration, performance qualification, and operational deployment while diagnosing timing and synchronization issues.

Design, develop, test, debug, and deploy system and embedded software. Provide application administration and end-user support, perform root-cause analysis for network/OS issues, integrate third-party components, review code, maintain monitoring systems, support cross-functional teams, and provide limited after-hours/on-call support.

Own and maintain the backend stack: build APIs and services in Node.js, manage deployments with Docker/Linux, design scalable REST APIs with Swagger, collaborate with hardware/frontend teams, and prepare sensor datasets for AI/ML pipelines with an eventual path to Lead AI Engineer.

Build and operate core backend services, APIs, and platform components for enterprise AI; integrate LLMs, retrieval and agent workflows; ensure reliability, observability, testing, and scalability; collaborate with research, product, and design to productionize AI capabilities.

As a DevOps Engineer, you will design, develop, and deploy scalable SaaS solutions, automate infrastructure tasks, and collaborate on CI/CD enhancements.

Join Ema as a Software Engineer to design and develop user interfaces for web applications, collaborating with product managers and UX designers, and integrating APIs.

As a Full-Stack Software Engineer, you will build end-to-end features, develop backend services, and create frontend applications while using AI-assisted tools and collaborating with teams.

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 Machine Learning Engineer, you will develop models for NLP and code-generation systems, analyze data, and improve AI performance using advanced algorithms. You'll manage the entire ML lifecycle and ensure effective communication of model benefits across the organization.

Develop and maintain scalable, reliable back-end systems and APIs, write maintainable code, and collaborate with global teams in a hybrid work environment.

Design and develop user interfaces and backend architectures for web applications, ensuring seamless integration and optimal performance using modern web technologies.

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.

The Software Engineer will manage data collection and ingestion for AI model training, enhance cloud infrastructure on GCP, and work closely with AI scientists.

Design and implement MAC control-plane software for satellite point-to-point and point-to-multipoint links. Develop schedulers, admission-control, state machines, QoS, flow control, and link-adaptation logic. Define interfaces to PHY/modem/hardware, evaluate centralized vs. distributed architectures, build simulation and test capabilities, and lead development through hardware integration, qualification, and deployment.

Build and maintain ML training and inference infrastructure, model APIs, and design pipelines. Partner with ML and protein design scientists to convert research into reproducible tooling and production services. Optimize compute and storage, implement CI/CD, monitoring, and follow engineering best practices to scale and accelerate protein design workflows.