26 to 50 of 90 Permanent JAX Jobs

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 ❯

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 ❯

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 ❯

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 ❯

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: 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: 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: 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: 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: 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 ❯

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 ❯

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 ❯

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 ❯