Top Tech Jobs & Startup Jobs

Build and maintain high-performance distributed inference systems to serve LLMs at scale. Implement intelligent request routing, autoscaling, load balancing, deployment pipelines, and integrate diverse AI accelerators across multi-cloud environments. Use observability to tune production performance and enable research workflows.

Four-month, full-time research fellowship focused on ML systems and performance. Fellows build and evaluate infrastructure-heavy projects (e.g., CPU simulators, accelerator backends, large-scale distributed training), use external models/APIs, receive mentorship, funding for compute, and aim to produce public research outputs.

Four-month full-time research fellowship mentoring fellows to run empirical RL and LLM projects using external infrastructure. Fellows receive compute funding and a weekly stipend, produce public outputs (e.g., papers), and work on RL environments, algorithms, model fine-tuning, and training/evaluation of large models with mentor support.

4-month full-time funded research fellowship using external models/APIs to produce public outputs (papers). Fellows receive mentorship, workspace access (Berkeley or London) or remote options within US/UK/Canada, weekly stipend, compute funding, and are expected to implement experiments, collaborate with mentors, and communicate results. Applicants must be fluent in Python and authorized to work in the US, UK, or Canada.

As an Enterprise Account Executive, drive revenue growth by securing strategic deals with enterprises and refining sales methodologies. Collaborate with teams to enhance product offerings, expanding market presence through innovative sales strategies. Ideal candidates will have extensive enterprise sales experience with emerging technologies, strong communication skills, and a passion for AI safety.

Four-month full-time research fellowship supporting empirical AI safety projects using external models and APIs. Fellows receive mentorship, compute funding, and workspace access to produce public outputs (e.g., papers) across safety, robustness, interpretability, RL, and societal-impact topics.

Lead architecture, roadmap, and implementation for feature flagging, dynamic configuration, and A/B/experimentation infrastructure. Build scalable distributed systems, libraries, tooling, and APIs/CLI to enable safe rollouts, experiments, and measurement across research and production. Partner with deployment, testing, and internal teams to define standards and improve developer productivity.

Lead technical strategy and build agent runtime platform and tooling to enable agentic productivity. Ship scalable, reliable infrastructure, develop agent harnesses and evals, collaborate cross-team, and define quality and operational practices.

Lead design and delivery of end-to-end vertical AI products (financial services, science, healthcare, enterprise). Partner with research to productionize models, engage enterprise customers, set technical direction, mentor engineers, and drive cross-team product development from 0→1 and through growth.

As a GPU Performance Engineer, you will develop and implement systems for GPU optimization, enhancing performance for large language models, and addressing complexities in hardware and software integration.