1 to 25 of 281 JAX Jobs

pipelines: data collection/cleaning, feature engineering, model training, validation, and inference. Rapidly prototype novel models (e.g., neural networks, probabilistic models) using PyTorch, TensorFlow, JAX, or equivalent. Productionize models in cloud/on-prem environments (AWS/GCP/Azure) with containerization (Docker/Kubernetes) and ensure low-latency, high More ❯

in AI research and applied machine learning. Expertise in key data science technologies and techniques, such as Python, Git, AWS, AWS Sagemaker, PyTorch, TensorFlow, Jax, Numpy, Scikit-learn, Time-series forecasting, Classification, Regression, Large-language models, and Experiment Design. Strong stakeholder management skills and the ability to communicate complex ideas More ❯

and optimize vector embedding generation pipelines using ScaNN or similar ANN techniques. Train, fine-tune, and deploy ML/DL models using TensorFlow, PyTorch, JAX, or similar frameworks. Collaborate with data engineers and solution architects to integrate models into scalable cloud solutions. Perform model evaluations, A/B testing, and More ❯

and optimize vector embedding generation pipelines using ScaNN or similar ANN techniques. Train, fine-tune, and deploy ML/DL models using TensorFlow, PyTorch, JAX, or similar frameworks. Collaborate with data engineers and solution architects to integrate models into scalable cloud solutions. Perform model evaluations, A/B testing, and More ❯

the analysis or application of data in finance, economics, or related fields is a plus. • Experience with machine learning libraries such as PyTorch, TensorFlow, JAX is a plus. • Experience applying generative AI solutions (via open source tools or through Azure, Amazon Bedrock, Nvidia etc.) is a plus. • Experience with cloud More ❯

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 to train and evaluate More ❯

versioning, testing, CI/CD, API design, MLOps) Building machine learning models and pipelines in Python, using common libraries and frameworks (e.g., PyTorch, MLFlow, JAX) Distributed computing frameworks (e.g., Spark, Dask) Cloud platforms (e.g., AWS, Azure, GCP) and HP computing Containerization and orchestration (Docker, Kubernetes) Ability to scope and effectively More ❯

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. Working at More ❯

. Knowledge of linear algebra, calculus and statistics equivalent to at least first-year university coursework. Experience exploring, analysing and visualising data. Experience using Jax, PyTorch, TensorFlow, NumPy, Pandas or similar ML/scientific libraries. In addition, the following would be an advantage: Experience with frontier LLM development. Experience collaborating More ❯

scaler platforms, e.g., AWS, Azure, GCP); building machine learning models and pipelines in Python, using common libraries and frameworks (e.g., NumPy, SciPy, Pandas, PyTorch, JAX), especially including deep learning applications; C/C++ for computer vision, geometry processing, or scientific computing; software engineering concepts and best practices (e.g., versioning, testing More ❯

especially Vertex AI (Workbench, Training, Prediction, Pipelines, Feature Store). • Proficiency in Python and strong experience with AI/ML frameworks (e.g., TensorFlow, PyTorch, JAX, Hugging Face Transformers). • Experience with data engineering and building robust data pipelines for AI/ML workloads on GCP (e.g., BigQuery, Dataflow). • Solid More ❯

especially Vertex AI (Workbench, Training, Prediction, Pipelines, Feature Store). • Proficiency in Python and strong experience with AI/ML frameworks (e.g., TensorFlow, PyTorch, JAX, Hugging Face Transformers). • Experience with data engineering and building robust data pipelines for AI/ML workloads on GCP (e.g., BigQuery, Dataflow). • Solid More ❯

especially Vertex AI (Workbench, Training, Prediction, Pipelines, Feature Store). • Proficiency in Python and strong experience with AI/ML frameworks (e.g., TensorFlow, PyTorch, JAX, Hugging Face Transformers). • Experience with data engineering and building robust data pipelines for AI/ML workloads on GCP (e.g., BigQuery, Dataflow). • Solid More ❯

complex ideas clearly Preferred: Experience in optimization, reinforcement learning, and/or large language models (LLMs) Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch, JAX) A strong publication record in top conferences (e.g., NeurIPS, ICML, ICLR, ACL) Why Join Us Work on groundbreaking AI research with real-world applications and More ❯

complex ideas clearly Preferred: Experience in optimization, reinforcement learning, and/or large language models (LLMs) Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch, JAX) A strong publication record in top conferences (e.g., NeurIPS, ICML, ICLR, ACL) Why Join Us Work on groundbreaking AI research with real-world applications and More ❯

learning, and/or large language models (LLMs) •Experience in chip design and applied AI research •Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch, JAX) Why Join Us •Work on groundbreaking AI research with real-world applications and a strong commitment to open-source contributions and scientific advancement •Collaborate with More ❯

are: Degree in computer science, electrical engineering, science, mathematics or equivalent experience. Extensive software engineering experience, particularly with Python-based scientific libraries such as JAX, PyTorch, TensorFlow, NumPy. Familiarity with machine learning and RL, plus the mathematics and statistics knowledge needed to follow relevant research papers (linear algebra, calculus, etc More ❯

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 More ❯

Familiarity in statistical methods for Machine Learning (e.g. Bayesian methods, HMMs, graphical models, dimension reduction, clustering, classification, regression techniques, etc.) Familiarity with PyTorch, TensorFlow, JAX or similar frameworks Strong coding abilities in Python Preferred Qualifications Experience in the Architecture, Engineering, and/or Construction domains, including expertise with industry-specific More ❯

Familiarity in statistical methods for Machine Learning (e.g. Bayesian methods, HMMs, graphical models, dimension reduction, clustering, classification, regression techniques, etc.) Familiarity with PyTorch, TensorFlow, JAX or similar frameworks Strong coding abilities in Python Preferred Qualifications Experience in the Architecture, Engineering, and/or Construction domains, including expertise with industry-specific More ❯

especially Vertex AI (Workbench, Training, Prediction, Pipelines, Feature Store). Proficiency in Python and strong experience with AI/ML frameworks (e.g., TensorFlow, PyTorch, JAX, Hugging Face Transformers). Experience with data engineering and building robust data pipelines for AI/ML workloads on GCP (e.g., BigQuery, Dataflow). Solid More ❯

Git/version control Experience with Linux servers Bonus Skills Cloud development experience (GCP and/or AWS) Time series knowledge Rust, Polars, PyTorch, Jax, Equinox, Flax, Cuda Other than these skills, we don't expect you to have everything required for this job out of the box. We will More ❯

regression techniques, etc.) Familiarity with Deep Learning techniques (e.g. Network architectures, regularization techniques, learning techniques, loss-functions, optimization strategies, etc.) Familiarity with PyTorch , TensorFlow , JAX or similar frameworks Strong coding abilities in Python and/or C++ Preferred Qualifications: 2D & 3D Generative AI Reinforcement Learning LLMs and Natural Language Processing More ❯

Familiarity in statistical methods for Machine Learning (e.g. Bayesian methods, HMMs, graphical models, dimension reduction, clustering, classification, regression techniques, etc.) Familiarity with PyTorch, TensorFlow, JAX or similar frameworks Strong coding abilities in Python Preferred Qualifications Experience in the Architecture, Engineering, and/or Construction domains, including expertise with industry-specific More ❯

regression techniques, etc.) Familiarity with Deep Learning techniques (e.g. Network architectures, regularization techniques, learning techniques, loss-functions, optimization strategies, etc.) Familiarity with PyTorch , TensorFlow , JAX or similar frameworks Strong coding abilities in Python and/or C++ Preferred Qualifications 2D & 3D Generative AI Reinforcement Learning LLMs and Natural Language Processing More ❯