Software Engineer, AI Compiler
Work across the full stack with software, systems, and hardware teams to ensure correctness, performance, and deployment readiness for real workloads. Contribute to shaping the long-term compiler architecture and tooling strategy. Design and implement parts of the compiler stack targeting the novel AI accelerator, including front-end lowering, IR transformations, optimization passes, and backend code generation. Build and evolve MLIR/LLVM based infrastructure to support graph lowering, hardware-aware optimizations, and performance-centric code emission. Collaborate closely with hardware architects, microarchitects, and research teams to co-design compiler strategies that align with evolving ISA and hardware constraints. Develop profiling and analysis tools to identify performance bottlenecks, validate generated code, and ensure high throughput/low latency execution of AI workloads. Enable efficient mapping of high-level ML models to hardware by working with model frameworks and graph representations such as ONNX, JAX, and PyTorch. Drive performance tuning strategies including kernel authoring, schedule generation, and hardware-specific optimization passes.
Software Intern
As a Software Engineering Intern at TensorWave, responsibilities include collaborating with senior engineers on features for cloud control plane, orchestration layer, user-facing APIs, or internal tooling; working on automation, monitoring, and observability for GPU clusters (Slurm + Kubernetes-native environments); participating in debugging performance bottlenecks in high-throughput inference or distributed training pipelines; writing clean, well-tested code and participating in code reviews; and learning how bare-metal AI clouds operate at scale, including hardware partitioning, high-speed networking, and storage.
Senior Software Engineer (Fullstack)
Lead the deployment, performance, and reliability of AI agents operating in live, high-stakes healthcare environments. Architect and scale full-stack systems integrating with EHRs, legacy healthcare platforms, and real-time voice infrastructure. Drive technical strategy for customer-facing solutions, collaborating with product and engineering to translate client needs into scalable architecture. Mentor engineers and set standards for code quality, testing, security, and HIPAA-compliant development. Shape product roadmap by identifying systemic challenges in customer workflows and proposing high-leverage technical solutions.
Senior Backend / Systems Engineer (AI) - San Mateo, CA
Design and build extensible backend systems that support flexible configurations for different customers and content types. Develop infrastructure that interfaces cleanly with large language models (LLMs), enabling prompt engineering, context injection, and modular evaluation workflows. Build tooling and platforms that enable fast iteration by AI engineers and analysts, including declarative pipelines, parameterized jobs, and reproducible experiments. Prioritize ease of deployment, integration, and testing, both for internal teams and external partners. Collaborate closely with product, data, and policy teams to translate nuanced safety needs into scalable, maintainable software systems.
Software Engineer - Sensing, Consumer Products
As a Software Engineer on Consumer Products Research, the responsibilities include building and shipping production software for sensing algorithms by translating algorithm prototypes into reliable end-to-end systems, implementing and owning key parts of the Python shipping pipeline including integration surfaces, evaluation hooks, and quality/performance guardrails. The role also involves developing embedded/on-device software in an RTOS environment (such as Zephyr) and deploying models to device runtimes and hardware accelerators. Additional responsibilities include optimizing real-time on-device perception loops for stability, latency, power, and memory constraints, creating data collection and instrumentation tooling to bring up new sensing modalities and accelerate iteration from prototype to dataset to model to device, and partnering cross-functionally with algorithms, human data, firmware/hardware teams to debug, profile, and harden systems against real-world variability.
Senior Software Engineer, ML Core
Design, develop, and deploy custom and off-the-shelf ML libraries and toolings to improve ML development, training, deployment, and on-vehicle model inference latency. Build tooling and establish development best practices to manage and upgrade foundational libraries such as Nvidia driver, PyTorch, TensorRT, to improve ML developer experience and expedite debugging efforts. Collaborate closely with cross-functional teams including applied ML research, high-performance compute, advanced hardware engineering, and data science to define requirements and align on architectural decisions. Work across multiple ML teams within Zoox, supporting in- and off-vehicle ML use cases and coordinating to meet the needs of vehicle and ML teams to reduce the time from ideation to productionization of AI innovations.
Software Engineer, Platform Systems
Design and build distributed failure detection, tracing, and profiling systems for large-scale AI training jobs. Develop tooling to identify slow, faulty, or misbehaving nodes and provide actionable visibility into system behavior. Improve observability, reliability, and performance across OpenAI's training platform. Debug and resolve issues in complex, high-throughput distributed systems. Collaborate with systems, infrastructure, and research teams to evolve platform capabilities. Extend and adapt failure detection systems or tracing systems to support new training paradigms and workloads.
Software Engineer, Platform Systems
Design and build distributed failure detection, tracing, and profiling systems for large-scale AI training jobs. Develop tooling to identify slow, faulty, or misbehaving nodes and provide actionable visibility into system behavior. Improve observability, reliability, and performance across OpenAI's training platform. Debug and resolve issues in complex, high-throughput distributed systems. Collaborate with systems, infrastructure, and research teams to evolve platform capabilities. Extend and adapt failure detection systems or tracing systems to support new training paradigms and workloads.
Engineering Manager – Foundational Data Systems for AI
Lead, mentor, and grow a team of senior engineers across multiple geographies; own hiring, onboarding, and career development in a high-bar engineering culture; set technical direction through design reviews, RFCs, and principled trade-offs; own the design and evolution of foundational systems including table maintenance and data layout, metadata, transactions, and schema evolution, distributed compute and orchestration, and reliability, observability, and operational tooling; translate strategy into execution through roadmaps and milestones; establish and uphold reliability, latency, and operational standards; lead incident response, postmortems, and continuous system improvement; partner closely with Research, Applied AI, Product, and Infrastructure teams to move ideas from research into production.
Freelance Software Developer (Kotlin) - Quality Assurance (AI Trainer)
Design and maintain automated tests to ensure the quality, performance, and reliability of Kotlin and Android applications. Collaborate with developers to identify, reproduce, and resolve functional, performance, and UI issues across multiple environments. Define and improve quality standards across build pipelines, ensuring smooth CI/CD integrations and release stability. Monitor app behavior in production and use data-driven insights to guide testing priorities and improvements. Flexibility and quick adaptation to new requirements are essential.
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