26 to 50 of 218 PyTorch Jobs in London

Level 6 or Level 7 AI/ML/Data Science apprenticeship programme. Core Skills & Competencies Technical Skills Programming proficiency in Python and common ML libraries such as TensorFlow, PyTorch, or similar. Experience with Jupyter Notebooks and version control (Git/GitHub). Basic understanding of supervised/unsupervised learning, neural networks, or clustering. Analytical Abilities Ability to interpret data More ❯

implementation. Experience with CSS frameworks and responsive design. Strong problem-solving skills and attention to detail. Nice to Have Experience with ML and/or computer vision frameworks like PyTorch, Numpy or OpenCV. Knowledge of ML model serving infrastructure (TensorFlow Serving, TorchServe, MLflow). Knowledge of WebGL, Canvas API, or other graphics programming technologies. Familiarity with big data technologies (Kafka More ❯

. Advanced experience with SQL for data querying and manipulation. Experience with Git, Bash, Docker, and machine learning pipelines. Experience with open-source machine learning libraries like scikit-learn, PyTorch, TensorFlow, and SciPy. Hands-on experience working with multi-modal data (images, text) and relevant ML techniques. Experience with cloud technologies and data storage solutions, including Snowflake. Understanding of personalization More ❯

NumPy, scikit-learn, etc.). Comfort working with large and complex datasets, including data wrangling and exploratory analysis. Experience (or strong interest) in GPU-powered model development (e.g. using PyTorch, TensorFlow, JAX, or similar). Demonstrated ability to work independently on real-world projects. Strong communicator, with the ability to share ideas, take feedback, and collaborate effectively. A master’s More ❯

NumPy, scikit-learn, etc.). Comfort working with large and complex datasets, including data wrangling and exploratory analysis. Experience (or strong interest) in GPU-powered model development (e.g. using PyTorch, TensorFlow, JAX, or similar). Demonstrated ability to work independently on real-world projects. Strong communicator, with the ability to share ideas, take feedback, and collaborate effectively. A master’s More ❯

NumPy, scikit-learn, etc.). Comfort working with large and complex datasets, including data wrangling and exploratory analysis. Experience (or strong interest) in GPU-powered model development (e.g. using PyTorch, TensorFlow, JAX, or similar). Demonstrated ability to work independently on real-world projects. Strong communicator, with the ability to share ideas, take feedback, and collaborate effectively. A master’s More ❯

NumPy, scikit-learn, etc.). Comfort working with large and complex datasets, including data wrangling and exploratory analysis. Experience (or strong interest) in GPU-powered model development (e.g. using PyTorch, TensorFlow, JAX, or similar). Demonstrated ability to work independently on real-world projects. Strong communicator, with the ability to share ideas, take feedback, and collaborate effectively. A master’s More ❯

ML systems in production environments, including ownership of key lifecycle stages: data collection, modeling, evaluation, deployment, and monitoring. • Proficiency in Python and modern ML and agentic frameworks such as PyTorch, TensorFlow, or LangChain, with experience packaging models into APIs or integrating them into applications. • A solid understanding of LLMs for natural language processing applications, including topics such as embeddings, prompt More ❯

across departments and navigate large organisations. Strong project management and organizational skills. Proficiency in programming languages such as Python, Java and Scala, and experience with ML frameworks like TensorFlow, PyTorch, and scikit-learn. Experience with cloud platforms (e.g., AWS), big data technologies (e.g., Spark) as well as other technologies used to deploy models to production (e.g., Kubernetes, GHA, Airflow, Docker More ❯

conferences (e.g., NeurIPS, ICML, ICLR, ACL,EMNLP, NAACL, ICLR) with specific focus on agent systems, tool use, or multi-agentcoordination Familiarity with one or more deep learning frameworks (e.g. pytorch, jax, tensorflow, ) Excellent communication skills to report and present research findings anddevelopments clearly, both orally and in writing. Curious and innovative disposition capable of devising novel, well-founded algorithmicsolutions to More ❯

Data Science with reasonable industry experience, or an MS with significant industry or research experience in the field • Extensive experience with machine learning and deep learning toolkits (e.g.: TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas) • Ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals • Experience with big More ❯

data science or software engineering. An excellent command of the basic libraries for data science (e.g. NumPy, Pandas, Scikit-Learn) and familiarity with a deep-learning framework (e.g. TensorFlow, PyTorch, Caffe) A high level of mathematical competence and proficiency in statistics A solid grasp of essentially all of the standard data science techniques, for example, supervised/unsupervised machine learning More ❯

field, or equivalent industry experience Experience with distributed systems for machine learning and deep learning at scale Strong knowledge of ML infrastructure and model parallelism techniques, including frameworks like PyTorch , Lightning, Megatron, DeepSpeed, and FSDPProficiency in Python and strong software engineering practices Experience with cloud services and architectures (AWS, Azure, etc.) Familiarity with version control, CI/CD, and deployment More ❯

learning or engineering roles. Strong expertise in Machine Learning and Deep Learning, with exposure to Reinforcement Learning as a plus. Proficiency in Python and modern ML libraries (e.g., TensorFlow, PyTorch, JAX, or Keras). Experience with version control systems (GitHub, GitLab) and knowledge of clean, maintainable coding practices. Familiarity with CI/CD pipelines for automating ML workflows. Ability to More ❯

production-grade code and a good understanding of data engineering & MLOps Solid understanding of machine learning concepts, familiarity working with common frameworks such as sci-kit-learn, TensorFlow, or PyTorch Collaborative and humble great teammate with an ability to work wimulti-functionalnal teams, including technical and non-technical stakeholders Passion for learning new skills and staying up-to-date with More ❯

Aimpoint Digital is a premier analytics consulting firm with a mission to drive business value for clients through expertise in data strategy, data analytics, decision sciences, and data engineering and infrastructure. This position is within our decision sciences practice which More ❯

operations (ideally, experience governing AI models in production environments) Expertise across cloud platforms (AWS, Azure, GCP), Kubernetes, and containerised systems. Strong technical skills in Python, Java/Go, TensorFlow, PyTorch, and data engineering. Proven ability to engage directly with CxO-level stakeholders. Experience in MLOps, AI governance, and large-scale deployment. Recognised professional certifications in AI or cloud technologies. If More ❯

operations (ideally, experience governing AI models in production environments) Expertise across cloud platforms (AWS, Azure, GCP), Kubernetes, and containerised systems. Strong technical skills in Python, Java/Go, TensorFlow, PyTorch, and data engineering. Proven ability to engage directly with CxO-level stakeholders. Experience in MLOps, AI governance, and large-scale deployment. Recognised professional certifications in AI or cloud technologies. If More ❯

operations (ideally, experience governing AI models in production environments) Expertise across cloud platforms (AWS, Azure, GCP), Kubernetes, and containerised systems. Strong technical skills in Python, Java/Go, TensorFlow, PyTorch, and data engineering. Proven ability to engage directly with CxO-level stakeholders. Experience in MLOps, AI governance, and large-scale deployment. Recognised professional certifications in AI or cloud technologies. If More ❯

operations (ideally, experience governing AI models in production environments) Expertise across cloud platforms (AWS, Azure, GCP), Kubernetes, and containerised systems. Strong technical skills in Python, Java/Go, TensorFlow, PyTorch, and data engineering. Proven ability to engage directly with CxO-level stakeholders. Experience in MLOps, AI governance, and large-scale deployment. Recognised professional certifications in AI or cloud technologies. If More ❯

fields. 3-5 years of experience in Machine Learning (ML), with expertise in crafting and reviewing production-grade Python code. Strong knowledge of ML frameworks and libraries (e.g., TensorFlow, PyTorch) and practical implementation of ML algorithms at a large scale. Experience in building applications with large language models (LLMs) and leveraging them to enhance AI solutions. Experience with distributed, high More ❯

deep learning algorithms including the latest multimodal foundation models and generative AI frameworks' exploration, development, and implementation. Extensive experience with common machine learning Python frameworks such as TensorFlow and PyTorch; and Python libraries such as pandas, and computer vision libraries such as OpenCV. Experience in ONNX and TensorRT. Very comfortable working in Linux environment. Familiarity with software development tools and More ❯

language processing, computer vision, deep learning, and other cutting-edge ML techniques. - programming skills in Python, R, or other relevant languages, and experience with popular ML frameworks like TensorFlow, PyTorch, or MXNet. - communication and collaboration skills to effectively work with cross-functional teams. PREFERRED QUALIFICATIONS - Proficient in any one of these areas: large language models, NLP (Information retrieval, Machine Translation More ❯

tuning Large Language Models or interactive AI applications (>1 year post-graduate experience); Technical proficiency in programming languages and frameworks commonly used in NLP and AI (e.g., Python, TensorFlow, PyTorch); Preferably several years of experience working with different AI capabilities and showcasing your passion both at work and outside work in the utilization of AI; Excellent communication skills to collaborate More ❯

into production environments at scale. Expertise in Python and relevant ML libraries. Strong experience with various ML algorithms (e.g., supervised, unsupervised, reinforcement learning) and deep learning frameworks (e.g., TensorFlow, PyTorch). Experience developing generative AI applications and deploying them into production. Experience working with cloud platforms, ideally Google Cloud Platform (GCP) and BigQuery. Proficiency in working with and querying global More ❯