Future Tech Jobs
Future Tech Jobs
Design and develop novel Transformer and GNN architectures for a unified foundation model that interprets relational databases and heterogeneous graphs. Work across the full ML lifecycle—from architecture design to inference optimization—on high-impact applications like fraud detection, forecasting, and recommendation systems. Collaborate with researchers to advance graph learning and relational reasoning in enterprise AI.
Develop and optimize foundational CUDA Core Libraries in C++ and Python, focusing on high-performance parallel algorithms, low-level GPU programming, and developer-facing APIs. Work across the stack to improve performance, tooling, and developer experience for HPC and AI applications. Collaborate in open-source-style workflows and engage directly with users to refine APIs and solve performance challenges.
The role involves designing and developing end-to-end systems using machine learning, deep learning, generative AI, and other advanced technologies to solve complex, real-world problems. Interns will create algorithms, deploy solutions into production, and collaborate with Amazon scientists. The position offers hands-on experience in a customer-focused environment with opportunities to publish research and contribute to impactful projects.
Engage in a 4-month full-time research project focused on reinforcement learning, mentored by Anthropic researchers. Work on empirical projects such as building RL environments for safety tasks or improving training data quality, with access to compute funding and a collaborative research environment. Output is expected to include public contributions like research papers.
A 4-month, full-time fellowship program offering mentorship and funding for technical talent to conduct empirical AI research aligned with Anthropic’s safety and security priorities. Fellows work on projects in areas like scalable oversight, adversarial robustness, or AI economics, with access to compute resources and a collaborative research environment. The program supports diverse backgrounds and encourages applications from underrepresented groups.
This role involves deep performance analysis and optimization of cloud and HPC workloads on NVIDIA's CPU architecture. You'll collaborate with developers, contribute to software stacks and libraries, and influence future CPU and software design. The position requires strong expertise in low-level programming and performance tuning, working across architecture, research, and product teams.
