Top AI Engineer Jobs

As a Staff Software Engineer, you will significantly enhance platform development and experimentation, focusing on AI integration and efficient software workflows. You'll manage end-to-end processes, develop core infrastructure, and employ AI coding agents to refine engineering practices, ultimately improving velocity and output quality.

Lead optimization of inference pipelines for large models, conduct research on hardware accelerators, and design high-performance inference frameworks. Mentor teams and drive technological innovation in AI inference optimization.

Lead the design of Agent-native platforms and build enterprise-grade knowledge bases while integrating LLM capabilities for AI-driven efficiency.

Responsible for researching AI hardware accelerators, optimizing performance for cloud computing environments, defining architecture, and analyzing technology trends.

Design, deploy, and maintain large-scale AI training and inference infrastructure. Scale distributed training, optimize GPU/hardware utilization, manage multi-cloud compute and orchestration, maintain MLOps tooling (MLflow), build high-throughput data pipelines, and partner with researchers and software engineers to productionize and monitor LLMs and other AI models.

Develop, test, debug, and maintain software systems while using AI-driven tools and prompt engineering as core engineering practices. Participate in incident resolution, impact analysis, monitoring/alerting, and continuous improvement; deepen AI tooling fluency and contribute to team knowledge sharing.

Lead design and implementation of an AI-native web platform, owning web framework, design system, CMS, CI/CD, infrastructure and SDLC agents. Define architecture, pioneer agentic workflows, set evaluation guardrails, mentor engineers, and drive cross-team technical alignment and migrations.

The Senior Software Engineer will enhance AI system reliability, performance, and scalability, focusing on distributed services and collaborating with ML researchers.

The Senior Data & AI Engineer will design, build, and deliver data-driven features, leveraging AI to improve user experiences, while collaborating with stakeholders and ensuring high-quality data solutions.

The Software Engineer will maintain and evolve the data platform, run LLM ETL pipelines, transform agent outputs, improve system reliability, and support incident response.

The AI Sales Engineer will manage customer interactions from demo to engagement, utilizing AI expertise to enhance customer experience and drive growth.

As an AI Product Engineer, you will develop innovative LLM-powered solutions, enhance AI systems, and collaborate with cross-functional teams to improve customer experiences.

Collaborate with product leaders to build scalable AI product features, mentor teammates, and shape engineering culture in a fast-moving environment.

Design, build, and operate the core AI platform, collaborating across teams to implement AI tools, ensure security, and enhance observability. Mentor junior engineers and contribute to the continuous improvement of product offerings using AI technologies.

Design and build internal platforms for model evaluation, regression testing, dataset discovery, secure large-scale data access, and agentic context curation. Own end-to-end product lifecycle, integrate customer feedback, ensure access controls and PII handling, and enable cross-team use of datasets and evaluation tooling.

The Principal Software Engineer leads the architectural design of a data platform, ensuring isolated and compliant data flows, overseeing AI data lakes, batch and streaming pipelines, and developing service APIs.

The Frontend Engineer will lead the development of a web application, focusing on architecture, feature development, and testing, while collaborating with other teams and optimizing performance.

The Senior AI/ML Applications Engineer will develop, integrate, and support AI-driven tools for IC design and verification, focusing on agentic AI methods to enhance productivity.

As a Senior Software Engineer, focus on backend development and AI integration for scientific applications, building systems that leverage advanced AI techniques.

The Principal AI/ML Engineer will lead the design, implementation, and deployment of AI systems, mentor junior engineers, and ensure model performance and reliability in production environments.

Responsible for defining and validating SoC IP blocks, collaborating with teams to ensure quality silicon for AI applications, and mentoring junior engineers.

Build and operate MLOps and agentic infrastructure: manage model registries, continuous training loops, and A/B testing; deploy agent microservices on Kubernetes; and create observability dashboards tracking token usage, latency, and agent reasoning.

Design, orchestrate, and optimize large-scale LLM pre-training runs across 1,000+ GPUs using PyTorch/DeepSpeed/Megatron-LM. Improve networking (InfiniBand/RDMA) and memory management, implement 3D parallelism, and automate checkpointing and failure recovery for month-long training jobs on SLURM or Kubernetes GPU clusters.

Operate and optimize large-scale LLM pre-training on 1,000+ GPU clusters using PyTorch, DeepSpeed, or Megatron-LM. Improve networking (InfiniBand/RDMA), memory management, checkpointing, and failure recovery. Manage SLURM/Kubernetes GPU clusters and apply systems engineering (C++, CUDA, Python) and 3D parallelism techniques.

Manage model registries, continuous training loops, and A/B testing infrastructure. Deploy agentic models as scalable microservices on Kubernetes and build observability dashboards to track token usage, latency, and agent reasoning paths. Maintain MLOps pipelines and ensure scalable, observable AI infrastructure.