ML Engineer Jobs

Senior AI Engineer responsible for designing, building, and deploying production AI/ML systems, including models, data pipelines, agentic systems, and RAG applications. The role combines hands-on engineering, architectural influence, and ownership of reliable, scalable AI delivery.

Build and scale the distributed inference systems that serve Claude to millions of users across diverse accelerators and cloud platforms. This role combines high-performance systems engineering, intelligent routing, fleet orchestration, and infrastructure for next-generation model research.

Sciforium is hiring a GPU Kernel Engineer to design and optimize custom GPU kernels powering large-scale AI training, inference, and serving systems. The role spans low-level accelerator programming, ML framework integration, and end-to-end performance optimization.

Build and operate the machine learning models and infrastructure that power fal’s trust and safety systems. You’ll improve harmful-content and abuse detection across a platform serving more than 1,000 models, with access to a large GPU cluster.

SOSi is seeking an AI/ML Engineer to develop, evaluate, deploy, and maintain machine learning models across generative AI, computer vision, NLP, classification, prediction, and reinforcement learning domains. The role combines model development, cloud deployment, data pipelines, experimentation, and technical communication in support of government initiatives.

Join Cerebras’s Core ML team to map emerging machine learning algorithms onto its wafer-scale architecture and determine how they perform across models, workloads, and hardware scales. The role combines performance modeling, benchmarking, prototyping, and hardware-software co-design to shape future AI systems.

Build high-performance ML runtimes and kernels that turn Core ML research ideas into efficient training and inference capabilities on Cerebras systems. The role spans frameworks, compilers, distributed execution, performance optimization, and low-level kernel development.

Lead the strategy and systems that measure, validate, and improve training data quality for reinforcement learning environments and frontier model training. This senior technical leadership role combines research, experimentation, production tooling, and mentorship.