76 to 100 of 104 TensorFlow Jobs in the East of England

in a technical discipline (e.g., computer science, chemistry, physics, engineering). Strong background in machine learning, including deep learning and generative models. Experience with ML frameworks such as PyTorch, TensorFlow, or JAX. Proficiency in Python and C++, with a collaborative mindset. Familiarity with protein structure modeling, co-folding, or related methods; knowledge of organic chemistry is a plus. Why More ❯

of modern machine learning, statistics, and computational modelling Experience leading teams and performing technical assurance across large R&D projects Strong Python skills and familiarity with frameworks like PyTorch, TensorFlow, scikit-learn Expertise in one or more of: computer vision, reinforcement learning, NLP/LLMs, knowledge graphs, RF/EO sensor data, autonomy Please note: Due to the nature More ❯

or autonomous agents NLP, LLMs, or knowledge graph technologies AI for RF/EW, radar, sonar, or acoustic domains Strong Python skills and familiarity with ML toolkits (e.g. PyTorch, TensorFlow, Scikit-learn) Experience with proposal writing (e.g. Dstl, NS, EPSRC) Prior involvement in engineering assurance, technical review, or QA of R&D outputs Security & Eligibility Due to the sensitive More ❯

BSc Degree in Engineering, Computer Science or Electronics; or equivalent experience. 5+ years of relevant experience. Solid practical experience of: Languages: Python, C/C++, OpenCL, CUDA ML Frameworks: TensorFlow, PyTorch, Caffe2, ONNX, OpenVx Linux Environment Task and Data parallel/concurrent systems AI Network optimisations: quantization, compression (pruning etc.) Experience developing and delivering on projects using best industry More ❯

CS/EE or related research experience in academia or industry We will consider various levels of experience in relevant research areas Key Skills: Experience with ML frameworks (PyTorch, TensorFlow, JAX) and efficient ML (incl. quantization, pruning, sparsification, distillation, etc.) Experience with deployment on embedded/mobile devices (such as smartphones, with mobile CPU, GPU, NPU) Experience with distributed More ❯

with a minimum of 4 years' postdoctoral or commercial experience Expertise in NLP, LLMs, graph machine learning, or semantic reasoning Proficient in Python and familiar with frameworks such as TensorFlow or PyTorch Experience leading technical teams and securing external R&D funding Benefits 10% annual bonus Hybrid working model with flexibility (minimum 2 days onsite) Access to high-impact More ❯

and memory architectures (e.g., SRAM, DDR, ROM, eFuse, HBM) HW-SW co-design Deep knowledge of any; VPU/NPU/GPU/CPU/TPU architecture ML frameworks - Tensorflow/PyTorch/Python or similar DSP algorithms - FIR/IIR filters or FFT... low-power, performance and optimisation Applicants must have UK/EU/France working rights More ❯

and memory architectures (e.g., SRAM, DDR, ROM, eFuse, HBM) HW-SW co-design Deep knowledge of any; VPU/NPU/GPU/CPU/TPU architecture ML frameworks - Tensorflow/PyTorch/Python or similar DSP algorithms - FIR/IIR filters or FFT... low-power, performance and optimisation Applicants must have UK/EU/France working rights More ❯

industry experience) in a relevant discipline. Extensive post-doctoral experience applying AI/ML to time-series or sequential data. Strong Python skills and familiarity with frameworks like PyTorch, TensorFlow, or scikit-learn. Proven ability to communicate complex results to technical and non-technical audiences. Desirable: experience in areas such as radar, EW, RF, sensor fusion, autonomy, or signal More ❯

in AI/ML or statistical signal processing • 4+ years post-PhD experience applying ML to sequential or sensor data • Strong Python development skills and fluency with ML libraries (TensorFlow, PyTorch, scikit-learn) • Expertise in time-series analysis, signal processing, or intelligent decision-making • Experience leading project teams and delivering R&D for defence, aerospace, or intelligence domains Desirable More ❯

and low-level system optimization - Proven track record of leading large-scale technical initiatives - Solid understanding of deep learning architectures (CNNs, RNNs, Transformers, etc.) - Experience with inference frameworks (PyTorch, TensorFlow, ONNXRuntime, TensorRT, LLaMA.cpp, etc.) - Strong communication skills and ability to work in a collaborative environment PREFERRED QUALIFICATIONS - Proficiency in kernel programming for accelerated hardware - Experience with latency-sensitive optimizations More ❯

Science or relevant experience in industry (PhD would be a plus!). Experience in the development of ML/AI applications using state-of-the-art toolchains, i.e. Pytorch, TensorFlow (Plus!). Familiarity with Cybersecurity: TARA, Attack Trees, HSM architectures. Exposure and familiarity with Reliability technologies, methodologies, and standards applied to SoCs, i.e. RAS, Predictive Maintenance, BFR, HTOL, HAST More ❯

to succeed. "Nice To Have": Experience in Cybersecurity technology projects (Plus!). Experience in the development of ML/AI applications using state-of-the-art toolchains, i.e. Pytorch, TensorFlow (Plus!). Experience with HW and SW Architecture Modelling. Model-Based System Engineering, ISO 15288, MagicGrid Framework, SysML 2.0 (Plus!). Exposure and familiarity with Reliability methodologies. Knowledge of More ❯

You will join an expert and motivated team responsible for crafting the next generation of Automotive and Industrial Architectures using innovative technologies, like AI, Chiplets, Quantum, etc. The role requires driving the HW and SW Architectures Safety and Security Concepts More ❯

/experience required for the Machine Learning Engineer job: MSc/PhD in a relevant field with strong ML/deep learning foundations Hands-on experience with PyTorch or TensorFlow Expertise in model training at scale and GPU systems Knowledge of model compression and optimization techniques A background in speech recognition would be beneficial This is a great opportunity More ❯

/experience required for the Machine Learning Engineer job: MSc/PhD in a relevant field with strong ML/deep learning foundations Hands-on experience with PyTorch or TensorFlow Expertise in model training at scale and GPU systems Knowledge of model compression and optimization techniques A background in speech recognition would be beneficial This is a great opportunity More ❯

signal processing, autonomy, and sensor fusion. Key Requirements: PhD or equivalent experience in AI/ML or statistical signal processing Strong Python programming and use of ML libraries (e.g., TensorFlow, PyTorch) Demonstrated experience with sequential data and real-time decision systems Ability to mentor junior colleagues and produce publishable R&D outcomes Benefits: 10% annual bonus Flexible hybrid working More ❯

scientific mindset. Strong academic background (2:1 or above) in STEM; postgraduate or R&D experience a bonus Excellent Python skills and hands-on experience with frameworks like PyTorch, TensorFlow, or JAX Experience building ML models in unique settings (e.g., constrained hardware or novel data) Familiarity with GPU processing (e.g., CUDA) and a range of ML techniques Bonus if More ❯

engineering ability, particularly around computational modelling for image analysis, image processing and/or machine learning (ideally CNNs for volumetric data). Increasingly, software architecture is a consideration. Python, TensorFlow, Keras, PyLattice or similar technologies would be indicative; additional languages such as C++ are also acceptable. Familiarity with computer vision, big data, geometric feature extraction, cellular imaging, timelapse imaging More ❯

support of commercial products An understanding of the latest trends in AI/ML research and development Good familiarity with one of the popular ML frameworks such as PyTorch, TensorFlow, JAX, ONNX, or PaddlePaddle A history of developer engagement or participation in an active open-source development community Experience in Product Owner roles, or a desire to grow into More ❯

engineering ability, particularly around computational modelling for image analysis, image processing and/or machine learning (ideally CNNs for volumetric data). Increasingly, software architecture is a consideration. Python, TensorFlow, Keras, PyLattice or similar technologies would be indicative; additional languages such as C++ are also acceptable. Familiarity with computer vision, big data, geometric feature extraction, cellular imaging, timelapse imaging More ❯

applying modern AI/ML methods (e.g., generative models, GNNs, active learning, foundation models)in a scientific context.- Strong coding skills and experience with relevant ML frameworks(e.g., PyTorch, TensorFlow, JAX) and chemistry toolkits (e.g., RDKit).- Deep understanding of molecular representation techniques and their application in modeling.- Experience in designing and implementing robust, scalable AI-driven workflows and More ❯

and generative models for the next. Requirements: Strong knowledge of Python and its use in machine learning including hands-on experience building products with modern ML frameworks such as TensorFlow and PyTorch Broad knowledge of machine learning techniques across multiple domains and the ability to transition into new domains quickly A top degree in a STEM subject UK national More ❯

and generative models for the next. Requirements: Strong knowledge of Python and its use in machine learning including hands-on experience building products with modern ML frameworks such as TensorFlow and PyTorch Broad knowledge of machine learning techniques across multiple domains and the ability to transition into new domains quickly A top degree in a STEM subject UK national More ❯

scientific mindset. Strong academic background (2:1 or above) in STEM; postgraduate or R&D experience a bonus Excellent Python skills and hands-on experience with frameworks like PyTorch, TensorFlow, or JAX Experience building ML models in unique settings (e.g., constrained hardware or novel data) Familiarity with GPU processing (e.g., CUDA) and a range of ML techniques Bonus if More ❯