1 to 25 of 30 Permanent TensorFlow Jobs in Cambridgeshire

Senior Machine Learning Research Engineer Salary: £62,860 - £84,070 Location: Cambridge - Triangle/Hybrid (2 days per week in the office) Contracts: 1x Permanent, Full Time (35 hours per week) 1x Fixed Term (18 months), Full Time (35 hours More ❯

MACHINE LEARNING RESEARCH ENGINEER Salary: £48,330 - £62,835 Location: Cambridge - Triangle/Hybrid (2 days per week in the office) Contract: Full Time (35 hours per week), Permanent Shape the future of AI-powered learning solutions with Cambridge University More ❯

MACHINE LEARNING RESEARCH ENGINEER Salary: £48,330 - £62,835 Location: Cambridge - Triangle/Hybrid (2 days per week in the office) Contract: Full Time (35 hours per week), Permanent Shape the future of AI-powered learning solutions with Cambridge University More ❯

including handling of large data sets, modelling and evaluation Good understanding of software engineering concepts, particularly with machine learning development Experience with machine learning Python frameworks such as PyTorch, Tensorflow and Scikit-Learn For more senior candidates: Understanding of, including published work within, related academic fields such as NLP, Computer Vision or Deep Learning Relevant industry experience with demonstrable More ❯

bayesian inference, causal reasoning & inference, transfer & multi-task learning, diffusion models, graph neural networks, active learning; Experience writing production-quality code with modern machine learning frameworks such as PyTorch, TensorFlow, JAX, or similar; Experience with multi-GPU and distributed training at scale; A team player who thrives in collaborative environments and is committed to enabling colleagues to reach their More ❯

Strong problem-solving skills, a proactive approach, and a keen understanding of software engineering best practices are essential. KEY RESPONSIBILITIES: Optimize Deep Learning Frameworks: Enhance and optimize frameworks like TensorFlow and PyTorch for AMD GPUs in open-source repositories. Develop GPU Kernels: Create and optimize GPU kernels to maximize performance for specific AI operations. Develop & Optimize Models: Design and … Compute Kernel (CK), CUTLASS, and Triton for multi-GPU and multi-platform performance. Deep Learning Integration: E xperience d in integrating optimized GPU performance into machine learning frameworks (e.g., TensorFlow, PyTorch ) to accelerate model training and inference, with a focus on scaling and throughput. Software Engineering: S kill ed in Python and C++, with experience in debugging, performance tuning More ❯

postdoctoral experience in machine learning Experience with patents or publications at top-tier peer-reviewed conferences or journals Experience with popular deep learning frameworks such as MxNet, PyTorch, or TensorFlow Experience in building large-scale machine learning systems Proficiency in state-of-the-art Natural Language Processing (NLP) and Computer Vision (CV) deep learning models Our inclusive culture empowers More ❯

Computer Science, or a related technical field (MSc with significant experience also considered). Extensive experience in designing, training, debugging, and evaluating machine learning models using frameworks like PyTorch, TensorFlow, or JAX. Strong foundation in mathematics and statistics, including linear algebra, probability, and optimization. Excellent scientific writing and communication skills. Preferred Qualifications Experience in computational biology, genomics, or drug More ❯

evidenced by publications and preprints. Strong breadth and expertise in Statistical analysis, machine learning, data visualization, programming (Python, R, etc.), data cleaning and data manipulation. Tools: Python, R, SQL, TensorFlow, Scikit-learn, Tableau, Power BI. Ability to generate high quality ideas and be self-driven to explore. Strong experience in programming and comfortable modifying existing code-base. Experience with More ❯

applying machine learning techniques to life science applications and datasets. Strong data processing and analysis skills. Confident coding in python and using common libraries (numpy, pandas, sklearn, pytorch/tensorflow, etc.) Experience building robust ML and data science pipelines. Experience with git version control, with familiarity of different branching and merging strategies. Compensation & Benefits At Insmed, we're committed More ❯

or equivalent research experience in industry or academia. Open to applicants across a range of seniority levels with relevant expertise. Core Skills: Proficiency with ML frameworks such as PyTorch, TensorFlow, or JAX. Experience in efficient ML techniques (e.g., quantization, pruning, sparsity, distillation). Practical knowledge of AI deployment on embedded/mobile platforms, including CPUs, GPUs, and NPUs. Hands More ❯

machine learning - Experience in building machine learning models for business application - Experience in applied research PREFERRED QUALIFICATIONS - Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc. - Experience with large scale distributed systems such as Hadoop, Spark etc. Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is More ❯

Junior Machine Learning Research Engineer Salary: £40,000-£52,000 Location: Cambridge - Triangle/Hybrid (2 days per week in the office) Contract: Full Time/Permanent (35 hours per week) Shape the future of AI-powered learning solutions with More ❯

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 ❯

focused environment that values innovation, openness, and personal growth Skills & Experience: PhD in Computer Science, Electrical Engineering, or equivalent industry research experience Solid background in machine learning frameworks (PyTorch, TensorFlow, or JAX) Experience in efficient ML techniques: quantization, pruning, distillation Familiarity with deployment on mobile and embedded devices (e.G. Smartphones, mobile CPU/GPU/NPU) Strong skills in 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 ❯

knowledge of HW and SW design Developing and working with large software systems in programming languages like Python Knowledge of state-of-the-art deep learning libraries such as Tensorflow and Pytorch Training large deep learning models on powerful GPU-based systems, "Nice To Have" Skills and Experience: ML Model Optimization techniques targeted for resource constrained ARM edge compute 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 ❯

preferably AWS. Experience with HPC clusters and workload managers such as Altair Grid Engine. Proficiency in developing workflows for application builds and testing. Experience with setting up CUDA, OpenMPI, TensorFlow, and PyTorch. Familiarity with cloud services and technologies. Knowledge of InfiniBand or other fast interconnect technologies. A plus: Understanding of drug development processes and workflows commonly encountered in biotech 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 ❯

systems, and HW-SW co-design Ability to develop and work with large software systems in programming languages like Python Knowledge of cutting-edge deep learning libraries such as Tensorflow, and Pytorch Willing to learn and train large deep learning models on GPU-based systems Qualities that will help your application stand out: Experience with ML model design, optimization More ❯

Bash A desire to have a positive impact both within our team and the wider Arm ecosystem Strong understanding of machine learning fundamentals and frameworks such as PyTorch and TensorFlow 'Nice to have' abilities and knowledge: Performance evaluation experience and knowledge of potential pitfalls Knowledge of hardware modelling concepts, including configuration and latency definition files Graphics programming experience with More ❯

JOB AD: OverviewWork within our clients machine learning team to deploy and optimize models for applications like low-latency speech recognition and large language models (LLMs). Initial focus will be on improving our clients speech recognition model's training 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 ❯

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 ❯