1 to 25 of 80 PyTorch Jobs in Cambridge

with frontend frameworks such as React, Angular, or Vue.js and backend technologies including RESTful APIs, Django, or Flask. Expertise in machine learning frameworks like PyTorch or Scikit-learn. Good experience with Generative AI models and techniques, such as GANs or transformers. Good experience with OpenAI, bedrock models, cognitive services etc. More ❯

systems-level experience Proven track record of delivering AI solutions for complex scientific problems Experience with machine learning algorithms, deep learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn, spaCY), and data processing techniques. Demonstrated experience in developing and deploying machine learning models in production environments. Experience with AI Cloud Platforms (AWS More ❯

a solid understanding of algorithms and data structures. Proficiency in Python with hands-on experience using open-source ML frameworks such as scikit-learn, PyTorch, TensorFlow, or Keras. Extensive experience with Machine Learning and Deep Learning models (e.g., tree-based methods, CNNs, Transformers) and developing robust, production-ready ML systems. More ❯

testing large language model behaviour, prompting and building products with language models. Expert knowledge of Python and advanced ML/LLM frameworks (e.g., TensorFlow, PyTorch, LangChain, LlamaIndex, etc). Deep understanding of agentic AI concepts and frameworks (e.g., agentic design patterns, multi-agent systems, reinforcement learning) and their applications in More ❯

models in a Bayesian Optimization context (Gaussian processes, Bayesian Neural Networks) on small and large datasets. Strong experience in at least one ML framework (PyTorch/TensorFlow/Jax) and robust experience in Python data science ecosystem (Numpy, SciPy, Pandas, etc.) Experience using a cloud computing service to reduce runtime More ❯

degree in a quantitative field (e.g., Computer Science, Machine Learning, Statistics, Physics, Mathematics) or equivalent industry experience. Strong background in deep learning frameworks (e.g., PyTorch, TensorFlow, JAX). Experience with distributed computing platforms (AWS, GCP, Azure, or on-prem clusters). Ideal: Kubernetes and Docker experience for scalable, reproducible workflows. More ❯

technical mentoring experience. Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining ML pipelines and data pipelines. Proficiency in model … Docker and container orchestration (e.g., Kubernetes). Preferred Skills: Experience with feature stores (e.g., Feast, Tecton). Knowledge of distributed training (e.g., Horovod, distributed PyTorch). Familiarity with big data tools (e.g., Spark, Hadoop, Beam). Understanding of NLP, computer vision, or time series analysis techniques. Knowledge of experiment tracking More ❯

support interfaces for model interaction. Conduct testing and documentation. Requirements Experienced Python developer. Proficiency with machine learning libraries such as TensorFlow, HuggingFace, scikit-learn, PyTorch, Pandas, NumPy, SciPy. Experience with AWS (EC2, S3, SageMaker) or Azure/GCP equivalents. Experience designing, developing, and deploying scalable infrastructure (e.g., Apache Airflow, Luigi More ❯

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 More ❯

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 More ❯

at least 1 year focused on Generative AI and NLP. Strong programming skills in Python; proficient in libraries such as NumPy, Pandas, scikit-learn, PyTorch, TensorFlow. Proven experience building and scaling GenAI applications in production. Expertise in LLM architectures (OpenAI, LLaMA, Mistral, etc.) and RAG implementation. Familiarity with frameworks like More ❯

degree or equivalent qualification, or other evidence of equivalent knowledge. Professional or research experience in some of the following: ML/NLP tools like PyTorch, Scikit-learn, Transformer architecture and Neural Networks. Coding and software engineering in mainstream programming languages, such as Python. Statistical packages for data manipulation and in More ❯

related NLP techniques is a plus. Programming Skills: Proficiency in Python (preferred) or similar programming languages, with experience in ML/DL frameworks (e.g., PyTorch, TensorFlow). Research Software Engineering: Experience or strong interest, with a desire to work aligned with the principles of modern open source etiquette and workflows. More ❯

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 More ❯

source communities. Requirements Excellent programming abilities with experience in relevant languages (Python, Rust, C++ and/or Go) Experience with relevant libraries/tools (PyTorch, Tensorflow, Neo4j) and/or AI accelerators (GPU, TPU) is a plus Deep understanding of open source development processes (RFCs/proposals, GitHub pull requests More ❯

quantitative disciplines. Experience with MLOps practices and tools including version control, automated testing, and CI/CD. Experience in at least one ML framework (PyTorch/TensorFlow/Jax) and robust experience in the Python data science ecosystem. Experience with large language models (e.g. autoregressive LLMs) for biological sequences is More ❯

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 More ❯

but we’re open to junior candidates eager to learn. Tech Skills: Proficiency in Python , and experience with machine learning frameworks such as TensorFlow , PyTorch , or Scikit-learn . Healthcare Focus: Ideally, you have an understanding of healthcare data or a genuine passion for improving the health industry through AI. More ❯

Master's/PhD or equivalent experience in Machine Learning, Computer Science, Maths, Data Science, or related field. Proficiency in deep learning frameworks like PyTorch/JAX. Strong Python software development skills (nice to have C other languages). Familiar with deep learning fundamentals: models, optimisation, evaluation and scaling. Capable More ❯

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 More ❯

and VAE architectures. Experience with spatial and single-cell data modelling and their application to biological questions. Strong programming skills in Python, TensorFlow/PyTorch, and familiarity with AWS cloud infrastructure. Demonstrable track record of applying AI to solve complex biological challenges and translate outputs into biologically meaningful hypotheses. C More ❯

evaluation. Solid understanding of software engineering practices, particularly in the context of ML development. Hands-on experience with Python and ML libraries such as PyTorch, TensorFlow, and Scikit-learn. Familiarity with tools like Git, Docker, and cloud platforms (e.g., AWS, GCP, Azure). Qualifications (Preferred for Senior Roles) Expertise in … opportunities employer. We are on the client's supplier list for this role. Keywords AI Research, Machine Learning Engineer, NLP, Computer Vision, Deep Learning, PyTorch, TensorFlow, LLMs, Transformers, GANs, Reinforcement Learning, Data Science, Python, Cambridge AI Jobs, Applied AI, Research Scientist, Artificial Intelligence, ML Research, AI Innovation More ❯

to open research Requirements: • PhD or equivalent experience in ML, AI, CS, physics, or mathematics • Proficient in Python, C++, and deep learning frameworks (e.g., PyTorch, TensorFlow) • Solid grasp of ML techniques; independent and team-oriented mindset Preferred: • Experience in LLMs, reinforcement learning, or chip design • Familiarity with JAX and optimization More ❯

experience in ML, AI, CS, physics, or mathematics Strong publication record (NeurIPS, ICML, ICLR, etc.) Proficient in Python, C++, and deep learning frameworks (e.g., PyTorch, TensorFlow)Solid grasp of ML techniques; independent and team-oriented mindset Preferred : Experience in LLMs, reinforcement learning, or chip designFamiliarity with JAX and optimization frameworks More ❯

algorithms and systems. Key Requirements: A PhD in Natural Language Processing, AI, Electrical Engineering, or a related field. Experience with ML frameworks such as PyTorch, TensorFlow, or JAX. Strong programming skills in C++, C, or Python. Experience working with embedded or mobile devices. Ideally, 2+ years of industry experience post More ❯