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AI ACCELERATOR Most diseases are still poorly understood at a biological level. Despite decades of research, the causal mechanisms driving many conditions remain unclear, limiting our ability to identify the right…
Responsibilities Position Overview We are seeking a motivated AI/ML Engineer to build reliable, scalable systems and Generative AI and Agentic AI features, and build and deploy data-driven solutions for our…
LOCATION This is a remote position and can sit anywhere in the United States. All candidates must be willing to very frequently travel across the United States. JOB SUMMARY NetApp’s Solutions Architecture (SA) team…
Senior AI Engineer at the Technology Innovation Institute to design, fine-tune, and deploy LLMs, vision-language models, and autonomous agentic systems in production. The role blends research and engineering, using Python/C++, PyTorch, DeepSpeed/vLLM, CUDA, vector databases, and agent frameworks like LangChain.
Technology Innovation Institute is hiring an AI Engineer to design, fine-tune, and deploy LLMs, vision-language models, and autonomous agentic AI systems. Day-to-day work spans model training (LoRA/QLoRA, RLHF), scalable low-latency inference with DeepSpeed/vLLM/TensorRT, and production deployment using Python, C++, CUDA, and cloud/edge platforms.
Machine Learning Researcher at CFM, a quantitative asset management firm in Paris, building AI-based alpha models. The role blends ML research (model architectures, training recipes) with engineering of distributed, multi-GPU training pipelines using Python and PyTorch.
Senior ML Engineer in Novo Nordisk's R&D, turning machine learning, generative AI and agent prototypes into reliable, secure production services. Day to day: design, deploy and operate ML/LLM applications on Databricks, AWS and Azure, and establish MLOps/LLMOps practices for chronic-disease research.
Some careers have more impact than others. If you’re looking for a career where you can make a real impression, join HSBC and discover how valued you’ll be. We are currently seeking an experienced professional to join…
About FlightSafety International FlightSafety International is the world’s premier professional aviation training company and supplier of flight simulators, visual systems and displays to commercial, government and…
Requisition Number: 28730 Required Travel: 0 - 10% Employment Type: Full Time/Salaried/Exempt Anticipated Salary Range: $95,626.00 - $135,012.80 Security Clearance: Top Secret Level of Experience: Senior This…
Overview The Consortium for Clinical Research and Innovation Singapore (CRIS), a wholly owned subsidiary of MOH Holdings, was established in 2020 with the goal of strengthening synergies and promulgating strategies for…
Remote (Argentina-based) engineer who designs, deploys, and scales the infrastructure behind LLM training, fine-tuning, and inference — managing GPU compute, data pipelines, monitoring, and cloud costs. Core stack: Python, AWS, Docker/Kubernetes, Terraform, PyTorch and LLM serving frameworks.
Research Program Manager at Reflection, an AI research lab building open frontier models. Day to day you drive cross-functional programs for training infrastructure and cluster reliability across pre-, mid- and post-training, triage incidents, and keep GPU-scale training runs (e.g. Megatron-based) healthy and unblocked.
Builds and scales the distributed training infrastructure behind Reflection's frontier open-model pre-training: designing large training runs with researchers, optimizing GPU utilization, communication, and memory across thousands of GPUs, and debugging bottlenecks in the distributed training stack using frameworks like Megatron/DeepSpeed and NCCL.
Research software engineer on Reflection's core training infrastructure team: designing RL training loops, distributed multi-thousand-GPU training systems, and petabyte-scale data pipelines, turning research prototypes into production-grade systems for open frontier AI models. Based in London.
Technical lead on Reflection's Applied AI team owning end-to-end LLM post-training for enterprise customers: defining training strategies, building synthetic data and reward-modeling pipelines, running RL training and evaluations on multi-node GPU clusters, and deploying customized models to cloud, VPC, and on-prem environments.
Research engineer role on the pre-training team at Reflection, an AI lab building open foundation models. Day to day you run experiments on scaling laws, data processing, optimizers and model architecture, implement SOTA deep learning methods, and optimize large-scale distributed training infrastructure using Python and PyTorch.
Infrastructure engineer at Causal Labs, an AI startup building a Large Physics foundation model for causal prediction of physical systems. You design, scale, and debug distributed training systems across thousands of GPUs using PyTorch/JAX stacks (FSDP, DeepSpeed, Megatron) to make large-scale training fast and reliable.
Research engineer role building and training AI agents that learn to do physics via reinforcement learning, designing benchmarks/evals for scientific reasoning, and scaling distributed training infrastructure. Stack centers on modern ML frameworks (PyTorch/JAX), distributed training (Ray, XLA, Accelerate), and RL algorithms like PPO, SAC, and MuZero.
Machine Learning Researcher at Bland doing foundational research across the voice AI stack — text-to-speech, speech-to-text, LLMs, and neural audio codecs — taking models from theory through large-scale training to real-time production inference for enterprise AI phone agents.
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