16 of 16 Neural Network Jobs in Cambridge

inference and compiler stack. You will work at the intersection of large-scale systems, compilers, and deep learning, crafting how neural network workloads map onto future NVIDIA platforms. This is your chance to be part of something outstandingly innovative! **What you’ll be doing:*** Build, develop … models across platforms.* Benchmark, profile, and monitor key performance and efficiency metrics to ensure the compiler generates efficient mappings of neural network graphs to our inference hardware.* Collaborate closely with hardware architects and design teams to feedback software observations, influence future architectures, and codesign features that unlock ...

salaries, flexible working arrangements, and genuine job security. How It Works Step 1 – AI Engineering Fundamentals Start with the basics of AI, including neural networks and large language models, to build a solid foundation in AI engineering. Step 2 – Data Fundamentals Understand the data workflow, from collection ...

race, religion, colour, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. Tagged as: Academia, Natural Language Processing, Neural Networks, NLP, Speech Processing, United Kingdom #J-18808-Ljbffr ...

with ability to execute and prioritize well in a complex matrixed environment.Relevant areas of desired expertise:Molecular representation learning for small molecules, graph neural networks, geometric deep learning, property prediction for ADME PK, physiochemical properties, safety, de novo design, chemical space exploration, foundation models for chemistry, uncertainty quantification ...

advantage: A background in decision making (Bayesian optimization, bandits, reinforcement learning, active learning) and/or probabilistic modelling and methods (Gaussian processes, Bayesian neural networks, Variational inference, etc). Experience in numerical programming (Python/NumPy/Tensorflow/PyTorch). Experience or interest in applying machine learning ...

search or adsStrong CS fundamentals. Should be able to convert ideas to code with easeGood understanding of machine learning fundamentals like classification, deep neural nets, and sequence-based models. Familiarity with modern NLP stack and multi-modal representation learning is a plusWe'd love to see that ...

quality through maintainable software, automated testing, continuous integration, effective engineering processes and customer feedback.Required Skills and Experience :A strong understanding of neural-network architecture and model execution, including computational graph representation and transformation, operator dispatch, memory planning, backend partitioning and execution across heterogeneous hardware.Proven experience in hardware ...

through maintainable software, automated testing, continuous integration, effective engineering processes and customer feedback. Required Skills and Experience : A strong understanding of neural-network architecture and model execution, including computational graph representation and transformation, operator dispatch, memory planning, backend partitioning and execution across heterogeneous hardware. Proven experience ...

experience levels.The RoleWe’re growing our diverse team, and you’ll contribute to the development and verification of next-generation neural network hardware! Collaborating with experts across global design centers, you’ll help deliver Arm’s next-generation IP using sophisticated tools and methodologies.As a System Test … running test cases, and working with modern tools and infrastructure.We are a distributed team crafting and deploying advanced emulation environments for pioneering Neural Accelerators. Your work will help bridge the gap between silicon development and real-world deployment, improved system validation, and reducing time-to-market.You’ll collaborate ...

machine learning and quantum computing. The role is hands-on across research, design, coding, evaluation, and iteration. You'll design, train, and evaluate neural networks for quantum and classical directions, host and serve models (including LLMs), turn recent papers into code, and collaborate with quantum scientists and researchers ...

following: driver development, inference engines like llama.cpp or vLLM, performance analysis of ML and GenAI workloads, knowledge of Neural Network Processing Units (NPU) or Graphics Processing Units (GPU) and how they are used for ML. In Return: You will receive a competitive reward package which includes generous ...

life improving technologies.In the past you would have applied your Machine Learning techniques to a range of different applications. These could include deep neural networking, statistical signal processing, artificial intelligence, data science, machine learning or other complex fields.As you will be applying your development skills to a number ...

seeking System Test Engineers to advance neural network hardware verification and validation. You will contribute to verification strategy and own complex work packages across global design centers, delivering high-quality IP through advanced emulation environments. You will design test automation, run cases, and collaborate with architecture, design ...

following: driver development, inference engines like llama.cpp or vLLM, performance analysis of ML and GenAI workloads, knowledge of Neural Network Processing Units (NPU) or Graphics Processing Units (GPU) and how they are used for ML.In Return: You will receive a competitive reward package which includes generous stock ...

hands-on role sitting at the intersection of modern machine learning and quantum computing — with two complementary directions. ML for quantum — using neural networks and learning-based methods to accelerate quantum computation (e.g. circuit optimisation and compilation, error mitigation, calibration, variational-parameter optimisation, and surrogate modelling of quantum … processes). ML on/with quantum — building and adapting classical AI methods, including neural networks and large language models, so they can benefit from quantum hardware and algorithms. You don't need to be a world expert in either quantum or LLMs — but you should be genuinely ...

decision making, including Bayesian optimization, bandits, reinforcement learning, or active learning (advantage) Background in probabilistic modelling and methods, including Gaussian processes, Bayesian neural networks, or variational inference (advantage) Experience in numerical programming with Python, NumPy, TensorFlow, or PyTorch (advantage) Experience or interest in applying machine learning to solve … Work In Machine Learning Bayesian Optimization Numerical Programming With Python Experience With TensorFlow Or PyTorch ATS Optimization Keywords Hard Skills Probabilistic Modelling Bayesian Neural Networks Gaussian Processes Variational Inference Reinforcement Learning Active Learning Scalable Algorithms Machine Learning Research Statistical Analysis Algorithm Development Soft Skills Team Collaboration Constructive Feedback ...