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Lead a data-science team at an AV company, turning fleet, simulation, and ML data into safety metrics, release criteria, and autonomy-stack improvements for real-world transit deployments.
Build and deploy AI systems for edge and embedded environments, from R&D to production, focusing on model training, evaluation, optimisation, and MLOps to deliver real-world impact in demanding settings.
Designs and deploys advanced AI/ML systems (LLMs, agentic workflows, multimodal models) for government/commercial clients, optimizing for production, edge, and security.
Deploy, validate, and support Ethernet fabrics for AI and HPC clusters; troubleshoot L1-L4 network issues involving BGP, VLANs, MLAG, ECMP, optics, and underlay/overlay reachability.
Research Engineer building and training large language models from scratch for coding tasks, deploying them into production to power JetBrains' AI platform.
Senior ML engineer builds and optimizes AI-driven feature pipelines and model training systems for a deep-learning ad platform, using Python, Spark, Kafka, and PyTorch.
Builds and optimizes AI training pipelines and inference services for Fin's LLM-based customer support agent, focusing on GPU performance and scalable systems in Berlin.
Build and scale deep learning frameworks on PyTorch for distributed training, design data strategies for large-scale defence AI systems across GPU clusters.
This role involves developing autonomous flight software for unmanned aerial vehicles by integrating reinforcement learning agents into high-performance Rust and Python-based systems. Engineers will work on real-time decision-making pipelines, hardware-in-the-loop testing, and distributed systems to ensure reliable performance in demanding environments.
Helsing is seeking an AI Research Engineer to design and train large-scale foundational models for autonomous defense applications. The role involves the full model lifecycle, from data curation to training and evaluation, using Python and frameworks like PyTorch or JAX.
Builds the runtime and programming model for long-running AI agents that run for weeks across distributed infrastructure, focusing on durability, observability, and secure tool execution.
Title Platform & Infrastructure Engineer Location: Los Angeles, CA Work Mode: Hybrid Duration: 12 Month JOB DESCRIPTION Senior Platform & Infrastructure Engineer on the MLBots team, you will design, build, and operate…
The Senior Forward Deployed Solution Engineer will work directly with customers to design, deploy, and troubleshoot complex infrastructure architectures involving Kubernetes, AI/GPU systems, and cloud-native environments. This hands-on role requires deep technical expertise in automation and systems engineering to ensure successful customer outcomes and production readiness.
Designs and optimizes GPU-powered infrastructure for GenAI/LLM workloads, focusing on distributed training, performance tuning, and Kubernetes/OpenShift deployments.
Senior MLOps Engineer on NVIDIA's DSX Enablement team, building and deploying AI solutions on NeoCloud/NCP platforms with focus on distributed training, inference optimization, and MLOps pipelines using Python, C++/Go/Rust, Kubernetes, and the NVIDIA stack.
Lead end-to-end deep learning and graph neural network solutions on Databricks Lakehouse, driving AI strategy and mentoring teams at a major grocery retailer.
Build and operate scalable ML training systems and pipelines on AWS and Kubernetes, optimizing GPU-based workloads, enabling Gen AI/LLM fine-tuning workflows, and improving platform reliability and developer experience.
Why choose us? Are you ready to take the next step in your career? Join us for an exciting opportunity at Albertsons Companies, where innovation and customer service go hand-in-hand! At Albertsons Companies, we are…
Build and maintain MLOps infrastructure for freight-intelligence models, automating monitoring, retraining, and deployment at scale in a logistics-focused product team.
Build and scale Reddit’s next-gen ML embedding platform, designing distributed training and low-latency serving systems that power personalized recommendations across the site.
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