101 to 125 of 203 PyTorch Jobs in the City of London

Hands on experience working within areas such as NLP, LLM, recommendation systems Information Retrieval stacks, GenAI (specifically RAG systems). Familiar with architecture and implementation of 1+ ML frameworks (PyTorch, scikit-learn). Experience working in the full model lifecycle (including experimentation, training, testing, monitoring, and deployment). Good knowledge of AWS’s machine learning infrastructure. Again this is a More ❯

Hands on experience working within areas such as NLP, LLM, recommendation systems Information Retrieval stacks, GenAI (specifically RAG systems). Familiar with architecture and implementation of 1+ ML frameworks (PyTorch, scikit-learn). Experience working in the full model lifecycle (including experimentation, training, testing, monitoring, and deployment). Good knowledge of AWS’s machine learning infrastructure. Again this is a More ❯

Machine Learning, Computational Biology, Bioinformatics, or related discipline (or equivalent industry experience) Demonstrated ability to apply ML methods to biological or genomic data Strong Python skills with experience in PyTorch, TensorFlow, or scikit-learn Understanding of bioinformatics workflows (e.g. genome assembly, QC, annotation) Experience working with large or complex genomic datasets Familiarity with model evaluation, benchmarking, and explainability Ability to More ❯

Deep expertise in search and recommendation systems (e.g., semantic embeddings, learning-to-rank, personalisation algorithms). Hands-on experience with modern ML toolchains — Python, Spark, and frameworks such as PyTorch or TensorFlow. Strong grounding in experimental design, A/B testing, and the use of offline/online metrics to guide product strategy. Excellent communication and stakeholder management skills, with More ❯

Deep expertise in search and recommendation systems (e.g., semantic embeddings, learning-to-rank, personalisation algorithms). Hands-on experience with modern ML toolchains — Python, Spark, and frameworks such as PyTorch or TensorFlow. Strong grounding in experimental design, A/B testing, and the use of offline/online metrics to guide product strategy. Excellent communication and stakeholder management skills, with More ❯

consultancy, or fast-paced business. Strong programming skills in Python, with experience building automation workflows, APIs, and data pipelines. Exposure to AI/ML frameworks (e.g. OpenAI, LangChain, TensorFlow, PyTorch). Solid knowledge of SQL and data warehousing concepts. Demonstrated experience with cloud platforms ( GCP & Azure preferred). Strong understanding of data modelling, transformation, and orchestration (e.g. dbt, Airflow, Azure More ❯

requirements, and operational challenges. Hands-on expertise with cloud platforms (AWS, Azure, Google Cloud) and scalable, secure data infrastructures. Skilled in analytics, problem-solving, and applying machine learning (TensorFlow, PyTorch, Scikit-learn) to business use cases. Excellent communication and stakeholder management, comfortable engaging with C-level executives. Please note that this role does not offer visa sponsorship If you’re More ❯

requirements, and operational challenges. Hands-on expertise with cloud platforms (AWS, Azure, Google Cloud) and scalable, secure data infrastructures. Skilled in analytics, problem-solving, and applying machine learning (TensorFlow, PyTorch, Scikit-learn) to business use cases. Excellent communication and stakeholder management, comfortable engaging with C-level executives. Please note that this role does not offer visa sponsorship If you’re More ❯

PhD (or MSc + equivalent experience) in Computer Science, Data Science, Mathematics, Physics, or Bioinformatics 5+ years post-qualification experience tackling complex technical challenges Expert-level Python programming (NumPy, PyTorch/TensorFlow, SciPy, pandas) Deep expertise in time-series and sequence modelling (RNNs, LSTMs, transformers, attention mechanisms) Strong foundation in probabilistic models (HMMs, Bayesian inference, graphical models) Track record of More ❯

4+ years’ experience in Machine Learning or AI , with exposure to LLM agent systems , tool-use frameworks, or generative AI. Advanced proficiency in Python and ML frameworks such as PyTorch or TensorFlow . Hands-on experience developing or fine-tuning LLaMA , GPT , or similar foundation models. Understanding of agentic architectures , chain-of-thought reasoning, and memory/reflection mechanisms. Proven More ❯

including prompt orchestration and tool calling. Retrieval-Augmented Generation (RAG) for dynamic context injection. Understanding of user-centric design for AI interfaces and intelligent automation. Experience with AI frameworks (PyTorch, Tensorflow, Hugging Face etc.). Preferred Skills Preferred knowledge of AWS, particularly AWS Bedrock for LLM deployment and orchestration. Self-motivated with a strong growth mindset. Pay range and compensation More ❯

including prompt orchestration and tool calling. Retrieval-Augmented Generation (RAG) for dynamic context injection. Understanding of user-centric design for AI interfaces and intelligent automation. Experience with AI frameworks (PyTorch, Tensorflow, Hugging Face etc.). Preferred Skills Preferred knowledge of AWS, particularly AWS Bedrock for LLM deployment and orchestration. Self-motivated with a strong growth mindset. Pay range and compensation More ❯

from concept to code without getting lost in the theory. You’ve already built or deployed real-world AI systems. You understand LLMs, NLP, and ML frameworks like TensorFlow, PyTorch, or LangChain. You know your way around Azure, AWS, or GCP, and you’re confident designing APIs, microservices, and data pipelines. Maybe you’ve come from an academic background and More ❯

from concept to code without getting lost in the theory. You’ve already built or deployed real-world AI systems. You understand LLMs, NLP, and ML frameworks like TensorFlow, PyTorch, or LangChain. You know your way around Azure, AWS, or GCP, and you’re confident designing APIs, microservices, and data pipelines. Maybe you’ve come from an academic background and More ❯

using Jira and Confluence (or similar). Able to work from design to implementation and back efficiently. Strong teamwork, communication, and problem-solving skills. Nice to Have: Experience with PyTorch or TensorFlow for AI-based perception or control. Exposure to distributed, embedded, or real-time systems. Knowledge of simulation tools like Gazebo or RViz. Experience with GPU programming (CUDA/ More ❯

using Jira and Confluence (or similar). Able to work from design to implementation and back efficiently. Strong teamwork, communication, and problem-solving skills. Nice to Have: Experience with PyTorch or TensorFlow for AI-based perception or control. Exposure to distributed, embedded, or real-time systems. Knowledge of simulation tools like Gazebo or RViz. Experience with GPU programming (CUDA/ More ❯

for data curation, versioning, and reproducible experimentation. You’ll Bring Strong experience with LLMs, generative, or multimodal models , ideally involving large-scale training or evaluation. Hands-on fluency in PyTorch, JAX, or TensorFlow , with experience in DeepSpeed, Megatron, FSDP, or similar . Understanding of distributed training, parallelism strategies , and scaling laws . Familiarity with post-training methods (RLHF, RLAIF, DPO More ❯

for data curation, versioning, and reproducible experimentation. You’ll Bring Strong experience with LLMs, generative, or multimodal models , ideally involving large-scale training or evaluation. Hands-on fluency in PyTorch, JAX, or TensorFlow , with experience in DeepSpeed, Megatron, FSDP, or similar . Understanding of distributed training, parallelism strategies , and scaling laws . Familiarity with post-training methods (RLHF, RLAIF, DPO More ❯

ML, Cloud Key Skills & Experience: 5+ years of experience within AI/ML Engineer Strong background in AI/ML Engineering Python expertise Knowledge of ML libraries such a PyTorch or TensorFlow Cloud platform experience (AWS, Azure or GCP) Experience working in production environments, shipping and building products This role is a hybrid role with 2-days a week required More ❯

product capability Remote first model Experience: Master’s degree in a Computing or AI-related discipline Strong Python skills and experience with machine learning or LLM frameworks (such as PyTorch, TensorFlow, or Hugging Face) Enthusiasm for building AI systems from the ground up in a small, ambitious team This is a chance to be part of a cutting-edge AI More ❯

ML/AI (recommendation systems, data mining, or similar). Proven track record of building or deploying GenAI/LLM systems into production. Strong Python skills, with experience in PyTorch or TensorFlow . Understanding of MLOps practices (evaluation, monitoring, scaling). Master’s (or equivalent experience) in Computer Science, AI, ML, or related field. ⭐ Bonus points for: experience designing annotation More ❯

A track record of building and scaling data science teams that deliver real impact Deep technical expertise in time-series ML, probabilistic modelling, or advanced analytics Proficiency in Python , PyTorch/TensorFlow , and modern ML tooling Experience translating research into deployed, production-ready solutions PhD (or equivalent) in a quantitative field 10+ years’ experience, with proven leadership across science and More ❯

ML/AI (recommendation systems, data mining, or similar). Proven track record of building or deploying GenAI/LLM systems into production. Strong Python skills, with experience in PyTorch or TensorFlow . Understanding of MLOps practices (evaluation, monitoring, scaling). Master’s (or equivalent experience) in Computer Science, AI, ML, or related field. ⭐ Bonus points for: experience designing annotation More ❯

A track record of building and scaling data science teams that deliver real impact Deep technical expertise in time-series ML, probabilistic modelling, or advanced analytics Proficiency in Python , PyTorch/TensorFlow , and modern ML tooling Experience translating research into deployed, production-ready solutions PhD (or equivalent) in a quantitative field 10+ years’ experience, with proven leadership across science and More ❯

/high-transactional computing environments. C++ and modern software engineering best practices. Cloud infrastructure (AWS, GCP, Azure, or similar). Exposure to or interest in machine learning frameworks (e.g., PyTorch, TensorFlow) — not essential but beneficial. Building and scaling complex systems end-to-end. C++/Embedded Software/ML/Machine Learning/Python More ❯