Rust Jobs

ClickHouse Labs is an applied research group focused on identifying and solving challenging problems in database systems, with a goal of advancing the state of the art and translating research into real-world system improvements. As a Research Scientist, you will tackle high-impact problems at the intersection of database systems, distributed systems, AI, and systems software engineering. You will collaborate with experienced researchers and engineers on a broad range of topics, including query optimization, execution engines, distributed systems, and emerging agentic workloads, working with leading open-source systems like ClickHouse and PostgreSQL. Your work will involve investigating performance bottlenecks, developing new algorithms and system designs, and evaluating them under realistic conditions, with opportunities to publish your work and contribute to open-source projects.

$175k - $235k

NVIDIA is seeking a System Software Engineer specializing in Agentic Retrieval to join our team at the forefront of the AI revolution. You will develop pipelines for indexing and querying multi-modal content, working with Generative AI, LLM, VLLM, and Agentic Retrieval technologies on our innovative hardware and software platforms. This role is crucial for accelerating containerized pipelines for high-quality multi-modal datasets and enhancing retrieval efficacy. You will focus on developing efficient, scalable systems for data processing, deduplication, filtering, and classification for tailored models, with an emphasis on iterative testing and improvement in system cost, speed, and accuracy through micro-optimization, prompt engineering, fine-tuning, and applying new research.

$184k - $357k

Anthropic

Reinforcement learning (RL) is crucial for Claude's ability to reason, write code, and act autonomously over long horizons. This role is part of the team responsible for building and maintaining the RL training system, which is used to train production models and for researchers across Anthropic to run their experiments. The team collaborates closely with research teams company-wide on the science and engineering required to scale RL effectively. As a Research Engineer, you will be at the heart of RL at Anthropic, with a direct view of RL training at the frontier, as the system you own supports both production and research runs. You will work with collaborators across research teams to understand system performance, identify areas of fragility, and drive future improvements.

$500k - $850k

SambaNova is seeking a Software Architect to join the SambaStack platform team. This role involves defining the technical direction and architectural strategy for an AI inference platform that serves enterprise AI workloads on SambaNova's RDU hardware. You will own cross-cutting architectural decisions, ensuring the platform meets enterprise-grade standards for scalability, reliability, and performance. This is a high-impact position at the intersection of AI infrastructure, enterprise software, systems architecture, and developer experience.

$245k - $325k

Harvey is transforming legal and professional services by integrating advanced agentic AI with an enterprise-grade platform. This role is a founding position on the Security Engineering team, focused on building the foundational security for AI agents. You will lead the development of a platform that enables agents to perform security work, including vulnerability discovery and validation through authorized penetration testing, while ensuring data and system protection. The work involves shaping how agents are sandboxed across product and internal platforms, building execution environments, orchestration, and controls, and enabling the secure internal use of open-source models.

$231k - $346k

Anthropic

Anthropic is dedicated to building AI systems that are safe, reliable, and steerable, aiming to benefit both users and society. This role is central to advancing Reinforcement Learning (RL), the core technology enabling Claude's reasoning, coding, and autonomous capabilities. The RL Scaling team focuses on how RL performance, stability, and learning efficiency evolve with increasing model size, episode length, and compute power. You will be instrumental in developing and scaling next-generation RL algorithms and architectures, from initial research to large-scale deployment, while deeply understanding and addressing the challenges that arise at scale. This position bridges research and engineering, requiring you to build the systems that accelerate iteration and experimentation, and to tackle complex, unsolved problems in Anthropic's largest RL runs.

$500k - $850k

Anthropic

Reinforcement learning is crucial for training AI models to reason, write code, and act autonomously. At scale, this process involves a demanding distributed system where training, sampling, and environment execution run concurrently across a large fleet of accelerators and hosts. This system must continuously exchange data and maintain progress despite hardware failures, shifting loads, and evolving research. The efficiency of this system directly impacts learning outcomes and the speed of research iteration. As a Research Engineer on the Distributed Systems team within RL Engineering, you will focus on the most critical bottlenecks within this system. This could involve areas like scheduling, data movement, sandboxed environment execution, storage, networking, fault tolerance, autoscaling, or observability. The role seeks generalist engineers capable of reasoning from first principles across different system layers and prioritizing impactful problems over familiar ones. The ideal candidate will have experience building and operating large distributed systems, a commitment to detail, and a desire to apply their expertise to a complex, heterogeneous, and rapidly changing workload.

$500k - $850k

Anthropic

Anthropic is building reliable, interpretable, and steerable AI systems to be safe and beneficial for users and society. The Cloud Inference team is responsible for scaling and optimizing Claude to serve massive audiences across AWS, GCP, Azure, and other cloud providers. This involves owning the end-to-end product on each platform, from API integration and intelligent request routing to inference execution, capacity management, and operations. Engineers on this team are highly leveraged, driving multiple revenue streams while optimizing compute resources. The role requires product-minded backend engineers who can navigate platform differences, design cross-provider services and abstractions, and make architectural decisions for reliability and cost-effectiveness at massive scale. The work directly contributes to increasing service scale, accelerating the launch of new models and features, and ensuring LLMs meet rigorous safety, performance, and security standards.

$320k - $485k

Anthropic

The Cloud Inference team is responsible for scaling and optimizing Claude to serve massive audiences of developers and enterprise companies across major cloud platforms like AWS, GCP, and Azure. Within this team, the model & inference launch team focuses on the validation pipeline for inference servers and load balancers. This critical infrastructure work ensures that every inference change, including new model launches and performance improvements, is deployed with correctness, performance, and reliability. The goal is to make validation fast, cost-effective, and trustworthy, directly impacting how quickly advanced models and features reach users on all cloud platforms and how efficiently compute resources are utilized.

$320k - $485k

Anthropic

Anthropic is dedicated to building reliable, interpretable, and steerable AI systems that are safe and beneficial for users and society. This role focuses on Multi-Agent systems, which are increasingly vital for AI deployment, from small subagents within products to large groups tackling complex problems. Training Claude for optimal performance and safety in these large groups is a challenging new frontier in reinforcement learning and a new way to scale compute at test time.

$500k - $850k

Cerebras is developing a new generation of disaggregated AI inference systems that combine GPU-accelerated prefill with ultra-fast decode on the Cerebras Wafer-Scale Engine. We are seeking a Software Engineer to build and enhance the ML API layer, making this heterogeneous serving system accessible, reliable, and user-friendly. You will operate across our inference APIs, model integration layer, request-routing services, and the Cerebras inference platform to ensure a consistent experience across various models and accelerator backends. This role is at the intersection of machine learning systems, API design, model serving, and distributed systems, enabling new model architectures and inference capabilities while defining stable user-facing behavior and ensuring features like streaming, sampling, tool use, structured outputs, and multimodal inputs function correctly in production.

Together AI

Together AI is building the Inference Platform to deliver advanced generative AI models, powering multi-tenant serverless workloads and dedicated endpoints. This platform enables developers, enterprises, and researchers to utilize the latest LLMs and multimodal models at scale. The role focuses on optimizing latency and maximizing the utilization of tens of thousands of GPUs. You will collaborate directly with research teams to productionize frontier models and engage with the open-source community, contributing to and leveraging projects like SGLang and vLLM to enhance inference performance and efficiency.

$200k - $290k

Together AI

Together AI is seeking a Machine Learning Engineer to join our Inference Engine team, focusing on optimizing and enhancing the performance of our AI inference systems. This role involves working with state-of-the-art large language models and ensuring they run efficiently and effectively at scale. You will have the chance to collaborate closely with AI researchers and engineers to create cutting-edge AI solutions and shape the future of AI inference.

$200k - $300k

Together AI

At Together AI, you will build and operate one of the world's largest GPU fleets for frontier model training and inference. This role is for engineers who excel at building systems, automating processes, and solving problems at a massive scale. If you prefer writing software over manual operations and aim to build infrastructure that autonomously manages tens of thousands of GPUs, we encourage you to apply.

$190k - $270k

Together AI

Together AI runs one of the largest GPU fleets globally, and the Infra Agent Systems team is responsible for developing the software that powers and automates this infrastructure. The team builds production AI agents designed to diagnose hardware failures, investigate incidents, correlate signals across the fleet, and automate operational workflows. Alongside these agents, they are building the core platform, which includes knowledge graphs, retrieval systems, orchestration frameworks, and developer tooling. This role offers the unique opportunity to work at the intersection of AI agents, distributed systems, infrastructure, and automation, tackling complex engineering challenges with significant real-world impact.

$250k - $300k

Labelbox is seeking a Member of Technical Staff to lead the design, development, and production of Frontier Data Products. This role involves building the essential sandboxed, reproducible environments that AI agents require for training and evaluation, including terminals, browsers, and tool-augmented workspaces. You will be responsible for writing production-quality infrastructure, integrating with the RL tooling ecosystem, and ensuring environments are robust and observable. A strong understanding of how RL training loops consume environments and potential failure points is crucial.

$140k - $200k

Thinking Machines is building AI that extends human will and judgment, and our Core Services team is responsible for the foundational infrastructure that enables models to run code, use tools, and take actions safely and reliably. This role involves designing, building, and operating a sandboxing platform where models can execute untrusted code and interact with tools. This is critical infrastructure that supports both internal research and external product development, requiring a focus on speed, security, and dependability.

$300k - $400k

Anthropic

The Safeguards ML Infra team is responsible for designing, building, and operating the production infrastructure that powers Claude's safety systems. This role is central to ensuring safeguards are properly configured and deployed for model launches, and owning the off-cycle deployment of new safety classifiers. The team ensures safety on the token generation path and manages the operational aspects of deploying these systems into production, including standing up safeguards for new model launches and deploying new safety classifiers. Every frontier model release goes through this team, which configures, verifies, and rolls out safeguards across all Claude platforms and leads incident response when issues arise. The goal is to automate manual checks into continuous validation and evolve launch runbooks into robust tooling.

$320k - $485k

Databricks

Databricks is seeking a Staff Software Engineer to join their AI Research Infrastructure team. In this role, you will be responsible for developing and operating the research stack that powers Databricks' AI research efforts. You will design and build services for scheduling, orchestrating, and observing large-scale training and inference experiment workloads across thousands of GPUs. Your work will involve improving developer tooling to ensure researchers can iterate quickly while maintaining reliability, efficiency, and security. You will collaborate closely with research scientists, ML engineers, and platform teams to transform experimental workloads into robust, repeatable pipelines and push the boundaries of the infrastructure's capabilities.

$199k - $270k

Anthropic

Anthropic is at the forefront of AI research, dedicated to developing safe, ethical, and powerful artificial intelligence. Our mission is to ensure that transformative AI systems are aligned with human interests. We are seeking a Staff level Engineer to join our Pre-training team, responsible for developing the next generation of large language models. In this role, you will work at the intersection of cutting-edge research and practical engineering, contributing to the development of safe, steerable, and trustworthy AI systems.

$500k - $850k