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AI Research Engineer
Designs and deploys advanced ML systems, moving research prototypes into production while ensuring scalability and reliability using Python and frameworks like PyTorch.
GPU Software Engineer (CUDA)
Design and optimize GPU-accelerated compute workloads using CUDA for AI training, inference, and high-performance computing, improving throughput and efficiency in production systems.
LLM Engineer
Designs, fine-tunes, and deploys large language models using PyTorch and distributed training, focusing on RLHF/DPO and robust evaluation pipelines.
AI Infrastructure Engineer
Optimize AI training and inference workloads for speed, cost, and efficiency across the full stack, from GPU kernels to distributed systems, using Python, C++, and profiling tools.
Staff Product Manager - ML Training Workflow
Define and drive the product strategy for ML training workflows that improve model development speed, training reliability, and developer productivity for GM’s autonomous vehicle platform.
Network Engineer, Design & Engineering
Design and build ultra-low-latency, lossless data-center fabrics for AI training and inference clusters, translating logical topologies into physical deployments across GPU platforms.
Staff Research Engineer (LLM Pre-Training)
Build and train large language models from scratch for coding assistance, deploying them to production across JetBrains’ developer tools ecosystem.
Senior Machine Learning Systems Engineer (Remote)
Build and scale ML platforms for Reddit’s Ads team, including offline experimentation, training orchestration, and agentic AI workflows to accelerate model development and deployment.
AI Research Engineer (Pre-training - LLM & Multi-Modal) - 100% Remote Worldwide
Research and develop large-scale pre-training pipelines for LLMs and multi-modal models, optimizing architectures, data curation, and distributed training on thousands of GPUs.
Senior Machine Learning Engineer
Senior ML Engineer builds and deploys production-scale personalization models (recommendations, send-time optimization) using Databricks, Spark, and Kubernetes to power Iterable’s AI-driven customer engagement platform.
Platform Engineer (Kubernetes)
Build and maintain a GitOps-native Kubernetes platform for AI workloads, including inference pipelines, distributed training, and GPU scheduling.
Principal Machine Learning Engineer
Principal ML Engineer at Grab’s AI Platform team, building and scaling ML infrastructure for Southeast Asia’s superapp, including LLM training/serving, fraud detection, and search ranking.
Principal Machine Learning Engineer
Principal ML Engineer builds and owns end-to-end AI systems: training pipelines, inference, evaluation, and deployment for a proactive conversational AI product.
Principal Machine Learning Engineer
Principal ML Engineer builds and scales production-grade AI systems for a proactive smart assistant, focusing on LLM training, inference, and deployment under real-world constraints.
AI Engineer Intern
Build and optimize distributed AI training and inference pipelines for gaming using PyTorch, DeepSpeed, and Kubernetes to support large language models and reinforcement learning workloads.
AI Engineer, AI & Applications
Build and optimize production-grade distributed training recipes (TorchTitan, Megatron) and benchmarking suites to improve AI model training efficiency for hyperscale customers.
Senior AI Research Engineer
Build and scale AI infrastructure for industrial automation, bridging research and production with MLOps and distributed systems.
Senior ML Engineer (AI Research, Physical AI)
Senior ML Engineer to research and build AI models for physical systems like robots, combining reinforcement learning, multimodal models, and real-world robotics in a collaborative research environment.