13 of 13 PyTorch Jobs in Crawley

language processing (NLP) techniques and developing custom solutions using large language models (LLMs) for business use cases. Proficient in Python-based AI/ML development using frameworks like TensorFlow, PyTorch, and Scikit-learn. LLM Orchestration and Development Expertise in building LLM-powered applications using frameworks such as LangChain and LangGraph, including prompt engineering, fine-tuning, and workflow orchestration. Skilled in More ❯

language processing (NLP) techniques and developing custom solutions using large language models (LLMs) for business use cases. Proficient in Python-based AI/ML development using frameworks like TensorFlow, PyTorch, and Scikit-learn. LLM Orchestration and Development Expertise in building LLM-powered applications using frameworks such as LangChain and LangGraph, including prompt engineering, fine-tuning, and workflow orchestration. Skilled in More ❯

language processing (NLP) techniques and developing custom solutions using large language models (LLMs) for business use cases. Proficient in Python-based AI/ML development using frameworks like TensorFlow, PyTorch, and Scikit-learn. Expertise in building LLM-powered applications using frameworks such as LangChain and LangGraph, including prompt engineering, fine-tuning, and workflow orchestration. Skilled in integrating LLMs with structured More ❯

on experience in computer vision (CV) or natural language processing (NLP); understanding of large language models (LLM) is a plus Skilled in object-oriented programming using Python. Familiar with PyTorch or other machine learning frameworks Excellent problem-solving skills Strong communication skills, both written and verbal Why work with us? Competitive salary commensurate with experience Highly attractive bonus scheme Initial More ❯

Scientist 's working across a variety of companies & industries Provide hands-on coding sessions and real-world project mentorship using Python and relevant ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch etc) Incorporate cloud-based tools and services (e.g., AWS, GCP, or Azure) into training to simulate modern ML engineering environments (Cloud Training can be provided to you) Keep training material More ❯

Excellent understanding of modern programming languages such as Ruby, Python, Perl, and Java developing ML models and automation scripts. Experience with popular ML frameworks and libraries, such as TensorFlow, PyTorch, Scikit-learn, and Keras. Understanding of algorithms and techniques for supervised and unsupervised learning. Experience with tools for model monitoring, logging, and performance evaluation, such as MLflow or Prometheus. Strong More ❯

Excellent understanding of modern programming languages such as Ruby, Python, Perl, and Java developing ML models and automation scripts. Experience with popular ML frameworks and libraries, such as TensorFlow, PyTorch, Scikit-learn, and Keras. Understanding of algorithms and techniques for supervised and unsupervised learning. Experience with tools for model monitoring, logging, and performance evaluation, such as MLflow or Prometheus. Strong More ❯

in digital signal processing (DSP) and machine learning applied to audio. Proficiency in programming languages such as Python, C++, and MATLAB. Hands-on experience with deep learning frameworks (TensorFlow, PyTorch, etc.). Understanding of real-time and embedded audio processing techniques. Experience working with generative AI models for audio synthesis and transformation. Strong problem-solving skills with the ability to More ❯

the data pipeline and MLOps practices for handling sensitive legal content securely. Required Experience: Solid experience with Python and ML/NLP libraries (e.g., spaCy, Hugging Face, TensorFlow/PyTorch). Experience building NLP or document analysis solutions, ideally for legal or compliance use cases. Strong understanding of legal language, structures, and workflows (e.g., contracts, clauses, case law). Knowledge More ❯

applications. Develop and deploy AI solutions using Azure Machine Learning services. Have a knowledge of top ML libraries scalable across multiple CPU’s and GPU’s. Such as TensorFlow, PyTorch, Keras, OpenAI, XGBoost. And have used these in a commercial setting. Troubleshoot and resolve issues related to data processing and AI model performance. Collaborate with cross-functional teams to understand More ❯

SRAM, DDR, ROM, eFuse, HBM) Hardware-Software co-design experience Knowledge of VPU/NPU/GPU/CPU/TPU architectures Experience with ML frameworks such as TensorFlow, PyTorch, Python, or similar Knowledge of DSP algorithms like FIR, IIR filters, or FFT Focus on low-power, performance, and optimization Note: Applicants must have UK/EU/France working More ❯

This role demands deep expertise in C and C++ programming, ML framework internals, compiler construction, and optimisation techniques. Key Deliverables: Implement Runtime: Build a runtime that seamlessly integrates with PyTorch, JAX, and TensorFlow (PJRT) for both training and inference execution patterns. The runtime must support asynchronous execution and multiple devices. Implement Compiler: Build a compiler that is extensible to future More ❯

successful use of Nscale’s training, fine-tuning, and inference APIs. Requirements 5+ years of experience building and deploying machine learning systems in production environments. Proficiency in Python and PyTorch, with a strong understanding of transformer architectures, LLMs, and multimodal generative models. Expertise in distributed training frameworks like DeepSpeed or Fully Sharded Data Parallel (FSDP). Experience with GPU programming More ❯