Top Tech Jobs & Startup Jobs in San Francisco Bay Area, CA

As an AI Researcher, you will develop novel architectures and optimizations in machine learning, collaborating with teams to enhance open models and ensuring cutting-edge research practices.

Design and build production systems for AI inference, optimize runtime services, and collaborate on AI solutions with researchers and engineers.

Develop systems and APIs for LLM inference and fine-tuning. Design production systems, collaborate with teams, and improve system efficiency.

The Senior Data Engineer will build and operate data infrastructure for high-volume event processing, enhance scalability, and collaborate with product teams on analytics systems.

The role involves developing and optimizing GPU-accelerated kernels for ML/AI applications, collaborating with teams to enhance AI systems' performance.

As a Forward Deployed Engineer, you will optimize inference engines and guide customers in deploying AI models effectively, ensuring high-value outcomes and driving product improvements.

The Staff Engineer will lead the architecture and development of Together's Customer Insights platform, focusing on analytics, event systems, and user workflows to enhance customer visibility and governance of AI workloads.

The role entails optimizing model performance and developer experience through serverless inference platforms, distributed systems, and API development. Responsibilities include enhancing system robustness and scalability, partnering with product teams, and maintaining clean software and IaC.

Translate RL and inference research into production systems to improve latency, throughput, cost, and model quality. Design and implement inference engines and scheduling, build RL/post‑training pipelines, profile and optimize GPU/network/memory performance, run scale experiments, and drive production roadmap and benchmarks. Provide technical leadership and mentor others.

The Senior Backend Engineer will optimize and build systems for the Inference Platform, focusing on low-latency, scalability, and performance for generative AI models. Responsibilities include enhancing request routing, developing auto-scaling systems, and collaborating with ML researchers to implement new model architectures in production.