Profile end-to-end latency, GPU utilization, memory pressure, and kernel efficiency with PyTorch Profiler, Nsight Systems, Nsight Compute, and torch.utils.benchmark, then improve throughput through ...
Profile end-to-end latency, GPU utilization, memory pressure, and kernel efficiency with PyTorch Profiler, Nsight Systems, Nsight Compute, and torch.utils.benchmark, then improve throughput through ...
Applied ML Engineer
Louisville, KY · On-site
ML frameworks (TensorFlow, PyTorch, scikit-learn). Feature store integration, model serving via low-latency APIs. • Key Skills: Model development, feature engineering, model serving infrastructure ...
Applied ML Engineer
Louisville, KY · On-site
ML frameworks (TensorFlow, PyTorch, scikit-learn). Feature store integration, model serving via low-latency APIs. • Key Skills: Model development, feature engineering, model serving infrastructure ...
$84K - $101K/yr
Experience with LLMs and PyTorch : Extensive experience with large language models and proficiency in PyTorch. Analytical and Problem-Solving Skills : Ability to address complex challenges in model ...
$84K - $101K/yr
Experience with LLMs and PyTorch : Extensive experience with large language models and proficiency in PyTorch. Analytical and Problem-Solving Skills : Ability to address complex challenges in model ...
Strong ML/computer vision (PyTorch/TensorFlow) * Deploying models to real-time or edge systems * Solid software engineering * U.S. person status (ITAR/EAR) required * Eligible to obtain and hold a U.
Strong ML/computer vision (PyTorch/TensorFlow) * Deploying models to real-time or edge systems * Solid software engineering * U.S. person status (ITAR/EAR) required * Eligible to obtain and hold a U.
Develop relationships with key players across PyTorch, Hugging Face, Ray, vLLM, Kubernetes, inference, training, agents, data, observability, MLOps, and the wider AI developer stack - turning them ...
New
Develop relationships with key players across PyTorch, Hugging Face, Ray, vLLM, Kubernetes, inference, training, agents, data, observability, MLOps, and the wider AI developer stack - turning them ...
New
$150K - $250K/yr
Python PyTorch TensorFlow AWS GCP Important: if an employer asks you to log into their system via iCloud or Google, send a code, an SMS or Telegram password, run some code, or install software ...
$150K - $250K/yr
Python PyTorch TensorFlow AWS GCP Important: if an employer asks you to log into their system via iCloud or Google, send a code, an SMS or Telegram password, run some code, or install software ...
$132K - $192K/yr
Utilize machine learning frameworks including Scikit- Learn, Pandas, PyTorch, TensorFlow, Keras, and AutoML tools. Utilize visualization tools including Matplotlib, Seaborn, Tableau, and Power BI.
$132K - $192K/yr
Utilize machine learning frameworks including Scikit- Learn, Pandas, PyTorch, TensorFlow, Keras, and AutoML tools. Utilize visualization tools including Matplotlib, Seaborn, Tableau, and Power BI.
$72K - $92K/yr
Ideal candidates have a robust research background with publications in leading conferences and skills in Python and ML frameworks like PyTorch. You will lead impactful projects, mentor researchers ...
$72K - $92K/yr
Ideal candidates have a robust research background with publications in leading conferences and skills in Python and ML frameworks like PyTorch. You will lead impactful projects, mentor researchers ...
Experience with deep learning, specifically NLP - PyTorch, HuggingFace, LLMs, etc. * Data science stack familiarity #J-18808-Ljbffr
Experience with deep learning, specifically NLP - PyTorch, HuggingFace, LLMs, etc. * Data science stack familiarity #J-18808-Ljbffr
$70 - $90/hr
Proficiency with standard ML frameworks (PyTorch, TensorFlow, scikit-learn, XGBoost) * Ability to critique ML claims against evidence and reproduce results Preferred Qualifications * Competition ...
$70 - $90/hr
Proficiency with standard ML frameworks (PyTorch, TensorFlow, scikit-learn, XGBoost) * Ability to critique ML claims against evidence and reproduce results Preferred Qualifications * Competition ...
SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection, data curation, reward model serving, and experiment ...
SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection, data curation, reward model serving, and experiment ...
Machine Learning Engineer
Covington, KY · On-site
SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection, data curation, reward model serving, and experiment ...
Machine Learning Engineer
Covington, KY · On-site
SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection, data curation, reward model serving, and experiment ...
SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection, data curation, reward model serving, and experiment ...
SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection, data curation, reward model serving, and experiment ...
Machine Learning Engineer
Lexington, KY · On-site
SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection, data curation, reward model serving, and experiment ...
Machine Learning Engineer
Lexington, KY · On-site
SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection, data curation, reward model serving, and experiment ...
SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection, data curation, reward model serving, and experiment ...
SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection, data curation, reward model serving, and experiment ...
Machine Learning Engineer
Owensboro, KY · On-site
SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection, data curation, reward model serving, and experiment ...
Machine Learning Engineer
Owensboro, KY · On-site
SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection, data curation, reward model serving, and experiment ...
Machine Learning Engineer
Louisville, KY · On-site
SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection, data curation, reward model serving, and experiment ...
Machine Learning Engineer
Louisville, KY · On-site
SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection, data curation, reward model serving, and experiment ...
SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection, data curation, reward model serving, and experiment ...
SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection, data curation, reward model serving, and experiment ...
SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection, data curation, reward model serving, and experiment ...
SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection, data curation, reward model serving, and experiment ...
SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection, data curation, reward model serving, and experiment ...
SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection, data curation, reward model serving, and experiment ...
Pytorch information
What is a PyTorch job?
A PyTorch job typically involves working with the PyTorch deep learning framework to develop, train, and deploy machine learning models. Professionals in this role may build neural networks, perform data preprocessing, optimize models, and integrate them into applications. These jobs are commonly found in AI research, software development, and data science, requiring expertise in Python, deep learning, and model optimization techniques.
What kinds of projects or tasks can a PyTorch developer expect to work on in a typical role?
As a PyTorch developer, you will likely work on developing, refining, and deploying deep learning models for tasks such as image recognition, natural language processing, or recommendation systems, depending on your company's focus. Your responsibilities may include data preprocessing, model architecture design, experimentation, performance tuning, and collaborating with data scientists and software engineers to integrate models into production systems. You might also be called upon to conduct research or prototype new algorithms, keeping up with the latest advancements in the AI field. Projects can vary from quick proofs of concept to large-scale deployments, offering diverse opportunities to grow your technical and collaborative skills.
What are the key skills and qualifications needed to thrive in the PyTorch position, and why are they important?
To thrive in a PyTorch developer role, you need a strong background in deep learning, programming (especially Python), and a solid understanding of machine learning fundamentals, often supported by a degree in computer science, engineering, or a related field. Experience with PyTorch, CUDA, cloud platforms (like AWS or Azure), and familiarity with data processing pipelines are highly valued, and certifications in AI or machine learning can be beneficial. Key soft skills include problem-solving, teamwork, and effective communication to collaborate with cross-functional teams and present technical results clearly. These skills are crucial for building robust machine learning models, ensuring reproducibility, and driving innovation in fast-paced, data-driven environments.
What are popular job titles related to Pytorch jobs in Kentucky?
For Pytorch jobs in Kentucky, the most frequently searched job titles are:
What job categories do people searching Pytorch jobs in Kentucky look for?
The top searched job categories for Pytorch jobs in Kentucky are:
Member of Technical Staff - ML Performance
On-site
Veeda Innovation
Other
Posted 7 days ago
Job description
Member of Technical Staff - ML Performance About Us
#J-18808-LjbffrVeeda AI is building the next generation of multimodal foundation world models for Physical AI. We're a small, fast-moving team of engineers and researchers from leading AI labs, tackling some of the most challenging problems at the intersection of AI, robotics, and embodied intelligence. If you're excited about pushing the boundaries of what's possible with Physical AI, you'll have the opportunity to make an outsized impact from day one.
Responsibilities-
Distributed Training Throughput: Own step time and model FLOPs utilization for multi-node video world model training, choosing the tensor, context, and expert parallelism mix in PyTorch FSDP2 and Megatron-Core rather than inheriting a default.
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Inference Throughput Optimization: Profile end-to-end latency, GPU utilization, memory pressure, and kernel efficiency with PyTorch Profiler, Nsight Systems, Nsight Compute, and torch.utils.benchmark, then improve throughput through torch.compile/Inductor, CUDA Graphs, mixed and low precision, quantization, operator fusion, and multi-GPU serving.
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Precision & Numerical Stability: Take BF16, FP8, and NVFP4 recipes from running to converging on Blackwell, chasing scaling-factor and accumulation bugs into the video tokenizer and VAE layers where the activation outliers actually live.
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Kernels & Compilation: Write and tune the CUDA and Triton kernels PyTorch does not give us, driving FlashAttention-4, FlexAttention, and torch.compile integration so quadratic attention over long video sequences stops setting step time.
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Communication & Overlap: Tune NCCL collectives and compute/communication overlap across NVLink domains and the fabric, using the NCCL flight recorder to turn a watchdog timeout into a named rank and collective, not a restart.
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Fault Diagnostics & Recovery: Build the detection layer for silent data corruption (SDC), stuck CUDA kernels, and "card-freeze" hangs, plus asynchronous and tiered checkpointing that makes an interruption cost minutes rather than a day.
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Bachelor's degree or equivalent hands-on experience in Computer Science, Computer Engineering, or a related technical field.
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Deep hands-on experience with PyTorch and at least one large-scale parallelism stack (FSDP2, Megatron-Core, TorchTitan, or DeepSpeed) on real multi-node jobs, not single-node approximations.
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Fluency in Python and C++/CUDA with the ability to predict where a kernel will stall from its memory access pattern before profiling.
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Experience profiling live training and inference runs with Nsight Systems or the PyTorch profiler and translating traces into quantifiable step-time or MFU improvements.
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Expertise in at least one of low-precision numerics, kernel authoring, or large-run fault diagnosis, and credibility in the others.
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Experience optimizing training or inference workloads across very large GPU clusters, including topology-aware placement, scaling efficiency, performance isolation, and diagnosing failures that emerge only at fleet scale.
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Experience writing Triton, CUTLASS, or CuTe-DSL kernels, or contributing to open-source kernel libraries.
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Experience implementing context or sequence parallelism for long-horizon video or high-token-count models.
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Experience running or porting large training workloads on AMD GPUs (ROCm) or Google TPUs (JAX/XLA).
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Experience building fault-tolerant training with elastic world size, dynamic node re-queueing, or asynchronous distributed checkpointing.
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Experience optimizing generative inference for interactive rollouts, including few-step samplers, distillation, and KV or latent caching.
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Publications or presentations on machine learning systems, compilers, or high-performance kernels.