Find your next AI Engineering role
1449+ open roles · 365+ companies hiring
1449 open positions
TPU Kernel Engineer
Anthropic
As a TPU Kernel Engineer, you will be responsible for identifying and addressing performance issues across various ML systems, including research, training, and inference. A significant part of this role involves designing and optimizing kernels specifically for the TPU. You will also provide crucial feedback to researchers regarding how model changes affect performance. The ideal candidate will have a proven history of solving large-scale systems problems and demonstrating expertise in low-level optimization.
$280k - $850k
Research Engineer/Research Scientist, Pre-training
Anthropic
Anthropic is seeking a Research Engineer to join its Pre-training team, focusing on developing the next generation of large language models. This role involves working at the intersection of cutting-edge research and practical engineering to build safe, steerable, and trustworthy AI systems. The team is dedicated to ensuring that transformative AI systems are aligned with human interests and are beneficial for society.
$350k - $850k
Research Engineer / Scientist, Alignment
Anthropic
Anthropic is seeking a Research Engineer/Scientist focused on AI alignment. This role involves designing and executing machine learning experiments to understand and steer the behavior of advanced AI systems, with a particular emphasis on safety and potential risks from future, highly capable AI. You will collaborate with teams like Interpretability and Fine-Tuning, contributing to exploratory research on topics such as scalable oversight, AI control, alignment stress-testing, automated alignment research, alignment assessments, safeguards research, and model welfare. The ideal candidate possesses a blend of scientific curiosity and engineering skill, aiming to make AI systems helpful, honest, and harmless.
$350k - $500k
Engineering Manager, GPU (ML Accelerator)
Anthropic
Anthropic's performance and scaling teams focus on making the most efficient and impactful use of compute resources for inference and training. As an Engineering Manager on these teams, you will be responsible for identifying and removing bottlenecks, building robust solutions, and maximizing system efficiency. You will also provide clarity, focus, and context to your team in a fast-paced, dynamic environment.
$500k - $850k
Staff Research Engineer, Discovery Team
Anthropic
Anthropic's mission is to create reliable, interpretable, and steerable AI systems that are safe and beneficial for users and society. The Discovery Team is focused on building an AI scientist capable of solving long-term reasoning challenges and advancing scientific frontiers. This role involves working across the entire model stack to identify and address key blockers on the path to scientific AGI, with a current focus on improving models' ability to use computers for long-horizon tasks and scientific workflows. You will be responsible for developing approaches to complex reasoning challenges, scaling research ideas, and creating evaluation frameworks to measure model capabilities.
$350k - $850k
Research Engineer, Production Model Post-Training
Anthropic
Anthropic's production models undergo sophisticated post-training processes to enhance their capabilities, alignment, and safety. As a Research Engineer on our Post-Training team, you'll train our base models through the complete post-training stack to deliver the production Claude models that users interact with. You'll work at the intersection of cutting-edge research and production engineering, implementing, scaling, and improving post-training techniques like Constitutional AI, RLHF, and other alignment methodologies. Your work will directly impact the quality, safety, and capabilities of our production models. This role may require responding to incidents on short-notice, including on weekends.
$350k - $500k
Research Engineer, Machine Learning (Reinforcement Learning)
Anthropic
As a Research Engineer within Reinforcement Learning, you will collaborate with a diverse group of researchers and engineers to advance the capabilities and safety of large language models. This role blends research and engineering responsibilities, requiring you to both implement novel approaches and contribute to the research direction. You'll work on fundamental research in reinforcement learning, creating 'agentic' models via tool use for open-ended tasks such as computer use and autonomous software generation, improving reasoning abilities in areas such as mathematics, and developing prototypes for internal use, productivity, and evaluation.
$500k - $850k
Research Engineer, Knowledge Team
Anthropic
We are seeking Research Engineers to reimagine how Claude interacts with external data sources. This role involves designing novel architectures for organizing information and training language models to leverage these architectures effectively. You will be instrumental in shaping the future of AI's interaction with knowledge bases, moving beyond human-centric constraints to unlock new possibilities for LLMs.
$350k - $850k
Performance Engineer
Anthropic
Anthropic is building reliable, interpretable, and steerable AI systems to ensure AI is safe and beneficial. As a Performance Engineer, you will tackle novel systems problems that arise from running machine learning algorithms at scale. Your role will involve identifying these challenges and developing systems to optimize the throughput and robustness of our large distributed systems. This position is ideal for individuals with a strong background in large-scale systems problems who are eager to deepen their expertise in machine learning.
$280k - $850k
Frequently asked questions
What counts as an AI Engineering job?
AI Job Board lists engineering roles that build, deploy, or operate AI/ML systems — including LLM engineering, RAG (retrieval-augmented generation), AI agents, prompt engineering, AI infrastructure and MLOps, model serving/inference, and fine-tuning. It excludes non-engineering functions like AI sales or marketing roles.
What is the difference between an AI Engineer and a Machine Learning Engineer?
An AI Engineer typically builds applications on top of existing models — LLM integration, RAG pipelines, agent orchestration, and prompt design. A Machine Learning Engineer more often trains, fine-tunes, or productionizes custom models. Many companies use the titles interchangeably, so search both when browsing.
Does AI Job Board include AI infrastructure and MLOps roles?
Yes. Titles such as AI Infrastructure Engineer, ML Platform Engineer, GPU Infrastructure Engineer, Inference Engineer, MLOps Engineer, and AI Site Reliability Engineer are all covered — these roles focus on the systems that serve and scale AI models rather than building models themselves.
Are remote AI and ML jobs available?
Yes. Filter by "Remote" on the jobs page to see fully remote AI/ML engineering roles, or browse the remote jobs feed directly.
What skills are most in demand for AI engineering roles?
The most commonly requested skills are LLM APIs (OpenAI, Anthropic, Gemini), RAG and vector databases (Pinecone, Weaviate, Qdrant), agent frameworks (LangGraph, CrewAI, AutoGen), inference/serving tools (vLLM, Ray Serve, TensorRT-LLM), and fine-tuning. Use the skill filters on the jobs page to browse by specific technology.
How fresh are the job listings?
Listings are sourced continuously from company career pages and refreshed automatically. Each job shows when it was posted, and the sitemap and API expose last-updated timestamps for every posting.
How much do AI Engineers get paid?
Compensation varies widely by role, seniority, and location. Where employers disclose a salary range, it is shown directly on the job listing — filter by salary range on the jobs page to narrow results to your target compensation.
