1 to 25 of 33 JAX Jobs in Central London

language) and in building data pipelines and ML models using modern libraries across multiple domains: Data science stack: NumPy, pandas/polars, scikit-learn, XGBoost, LightGBM Deep learning: PyTorch, JAX Statistical programming: NumPyro, PyMC Data skills: Proficient in SQL, with the ability to write efficient, maintainable queries and manage data pipelines for analytics and modeling workflows. ML Ops & deployment: Familiarity More ❯

language) and in building data pipelines and ML models using modern libraries across multiple domains: Data science stack: NumPy, pandas/polars, scikit-learn, XGBoost, LightGBM Deep learning: PyTorch, JAX Statistical programming: NumPyro, PyMC Data skills: Proficient in SQL, with the ability to write efficient, maintainable queries and manage data pipelines for analytics and modeling workflows. ML Ops & deployment: Familiarity More ❯

projects including training, fine-tuning, or production deployment Strong track record in scalable AI system development Technical Expertise Expert-level Python programming with deep knowledge of PyTorch, TensorFlow, or JAX Proven experience with distributed computing environments and modern MLOps workflows Practical knowledge of LLM toolkits (Hugging Face ecosystem, training frameworks) Strong problem-solving abilities for complex model performance and infrastructure More ❯

projects including training, fine-tuning, or production deployment Strong track record in scalable AI system development Technical Expertise Expert-level Python programming with deep knowledge of PyTorch, TensorFlow, or JAX Proven experience with distributed computing environments and modern MLOps workflows Practical knowledge of LLM toolkits (Hugging Face ecosystem, training frameworks) Strong problem-solving abilities for complex model performance and infrastructure More ❯

expertise: Skilled in building data pipelines and ML models using modern libraries across multiple domains: Data science stack: NumPy, pandas/polars, scikit-learn, XGBoost, LightGBM Deep learning: PyTorch, JAX Statistical programming: NumPyro, PyMC Data skills: Proficient in SQL, with the ability to write efficient, maintainable queries and manage data pipelines for analytics and modelling workflows. Model development & deployment: Familiarity More ❯

expertise: Skilled in building data pipelines and ML models using modern libraries across multiple domains: Data science stack: NumPy, pandas/polars, scikit-learn, XGBoost, LightGBM Deep learning: PyTorch, JAX Statistical programming: NumPyro, PyMC Data skills: Proficient in SQL, with the ability to write efficient, maintainable queries and manage data pipelines for analytics and modelling workflows. Model development & deployment: Familiarity More ❯

models in a distributed environment. LLMs: Understanding of LLM architectures, pre and/or post-training, evaluations and inference. Programming languages: Proficiency in Python using PyTorch/TensorFlow/JAX framework. Cloud-native technologies: Experience in developing and deploying in cloud platforms (e.g., AWS, GCP or Azure), an understanding of containerisation (e.g., Docker). Algorithms and data structures: Excellent understanding More ❯

models in a distributed environment. LLMs: Understanding of LLM architectures, pre and/or post-training, evaluations and inference. Programming languages: Proficiency in Python using PyTorch/TensorFlow/JAX framework. Cloud-native technologies: Experience in developing and deploying in cloud platforms (e.g., AWS, GCP or Azure), an understanding of containerisation (e.g., Docker). Algorithms and data structures: Excellent understanding More ❯

a distributed environment. LLMs: Strong understanding of LLM architectures, pre and/or post-training, evaluations and inference. Programming languages: Excellent proficiency in Python using PyTorch/TensorFlow/JAX framework. Customer facing: Experience working directly with customers to solve applied problems, including product integration. Cloud-native technologies: Experience in developing and deploying in cloud platforms (e.g., AWS, GCP or More ❯

a distributed environment. LLMs: Deep understanding of LLM architectures, pre and/or post-training, evaluations and inference. Programming languages: Excellent proficiency in Python using PyTorch/TensorFlow/JAX framework. Customer facing: Experience working directly with customers to solve applied problems, including product integration. Cloud-native technologies: Experience in developing and deploying in cloud platforms (e.g., AWS, GCP or More ❯

a distributed environment. LLMs: Strong understanding of LLM architectures, pre and/or post-training, evaluations and inference. Programming languages: Excellent proficiency in Python using PyTorch/TensorFlow/JAX framework. Customer facing: Experience working directly with customers to solve applied problems, including product integration. Cloud-native technologies: Experience in developing and deploying in cloud platforms (e.g., AWS, GCP or More ❯

a distributed environment. LLMs: Deep understanding of LLM architectures, pre and/or post-training, evaluations and inference. Programming languages: Excellent proficiency in Python using PyTorch/TensorFlow/JAX framework. Customer facing: Experience working directly with customers to solve applied problems, including product integration. Cloud-native technologies: Experience in developing and deploying in cloud platforms (e.g., AWS, GCP or More ❯

Reinforcement Learning (policy optimisation, reward modelling, RLHF). Hands-on experience training/fine-tuning generative models (LLMs, diffusion, transformers, GANs). Strong knowledge of deep learning frameworks (PyTorch, JAX, TensorFlow). Proficiency in Python and standard ML libraries. Solid foundations in probability, optimisation, and statistics. Experience working with large-scale distributed training on GPUs/TPUs. If this sounds More ❯

Reinforcement Learning (policy optimisation, reward modelling, RLHF). Hands-on experience training/fine-tuning generative models (LLMs, diffusion, transformers, GANs). Strong knowledge of deep learning frameworks (PyTorch, JAX, TensorFlow). Proficiency in Python and standard ML libraries. Solid foundations in probability, optimisation, and statistics. Experience working with large-scale distributed training on GPUs/TPUs. If this sounds More ❯

algorithms, optimisation, and model evaluation 📈 Strong mathematical reasoning and analytical problem-solving skills 🗣 Excellent communication skills and a genuine passion for learning and innovation Nice to Have: 💾 Experience with JAX , Hydra , or Weights & Biases 📊 Exposure to GANs , diffusion models , or autoregressive architectures 📚 Knowledge of data privacy , machine unlearning , or secure ML methods 💻 Internship or academic project experience in AI research More ❯

algorithms, optimisation, and model evaluation 📈 Strong mathematical reasoning and analytical problem-solving skills 🗣 Excellent communication skills and a genuine passion for learning and innovation Nice to Have: 💾 Experience with JAX , Hydra , or Weights & Biases 📊 Exposure to GANs , diffusion models , or autoregressive architectures 📚 Knowledge of data privacy , machine unlearning , or secure ML methods 💻 Internship or academic project experience in AI research More ❯

Collaborate cross-functionally with hardware, software and research teams. Requirements Strong background in machine learning algorithm development and optimisation. Proficiency in Python and modern ML frameworks such as PyTorch, JAX or TensorFlow. Experience with data modelling, preprocessing and performance benchmarking. Understanding of ML evaluation metrics and model analysis methods. Excellent communication skills and collaborative mindset. 3+ years’ experience in ML More ❯

Collaborate cross-functionally with hardware, software and research teams. Requirements Strong background in machine learning algorithm development and optimisation. Proficiency in Python and modern ML frameworks such as PyTorch, JAX or TensorFlow. Experience with data modelling, preprocessing and performance benchmarking. Understanding of ML evaluation metrics and model analysis methods. Excellent communication skills and collaborative mindset. 3+ years’ experience in ML More ❯

looking for 3+ years developing deep learning systems with shipped models or published research. Hands-on with Vision Language Models, LLMs or generative models. Strong Python + PyTorch/JAX skills (debugging, profiling, shipping). Passion for bridging the gap between simulation and reality. This is one of the most exciting and technically challenging roles I’ve see with the More ❯

looking for 3+ years developing deep learning systems with shipped models or published research. Hands-on with Vision Language Models, LLMs or generative models. Strong Python + PyTorch/JAX skills (debugging, profiling, shipping). Passion for bridging the gap between simulation and reality. This is one of the most exciting and technically challenging roles I’ve see with the More ❯

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, or More ❯

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, or More ❯

looking for 3+ years developing deep learning systems with shipped models or published research. Hands-on with Vision Language Models, LLMs or generative models. Strong Python + PyTorch/JAX skills (debugging, profiling, shipping). Passion for bridging the gap between simulation and reality. This is one of the most exciting and technically challenging roles I’ve see with the More ❯

looking for 3+ years developing deep learning systems with shipped models or published research. Hands-on with Vision Language Models, LLMs or generative models. Strong Python + PyTorch/JAX skills (debugging, profiling, shipping). Passion for bridging the gap between simulation and reality. This is one of the most exciting and technically challenging roles I’ve see with the More ❯

looking for 3+ years developing deep learning systems with shipped models or published research. Hands-on with Vision Language Models, LLMs or generative models. Strong Python + PyTorch/JAX skills (debugging, profiling, shipping). Passion for bridging the gap between simulation and reality. This is one of the most exciting and technically challenging roles I’ve see with the More ❯