1 to 25 of 46 Permanent JAX Jobs

implement end-to-end AI 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-availability inference. Strategic Leadership Develop More ❯

Science, Machine Learning, Mathematics, or a closely related field. Strong foundational knowledge of machine learning and deep learning , with hands-on experience using frameworks such as PyTorch , TensorFlow , or JAX . Exposure to LLM fine-tuning and/or experience working with transformer-based models (e.g. GPT, LLaMA, Mistral). Interest in or familiarity with agentic AI frameworks and multi More ❯

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 thrive More ❯

processing libraries (e.g., Pandas, Polars, NumPy). Hands-on experience in building and maintaining automated data pipelines for large-scale data processing. Familiarity with machine learning frameworks (e.g., PyTorch, JAX, scikit-learn) as applied to data quality and augmentation tasks. Expertise in working with healthcare data, including familiarity with the OMOP Common Data Model (OMOP CDM). Strong experience in More ❯

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 relevant More ❯

software development skills in R (including package development, deployment, advanced programming) and Python. Specialist expertise in one or more of the following: Deep learning & analytical frameworks such as pytorch, jax, tensorflow; LLM/LMM applications & agentic AI; bioinformatics & data science. Expertise in systems programming languages (e.g. C/C Rust) is optional but can be beneficial. Strong working knowledge of More ❯

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 or PhD More ❯

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 or PhD More ❯

may be a good fit if you: Have 5+ years of industry-related experience Are proficient in Python and have experience with deep learning frameworks such as PyTorch or Jax Have a strong software engineering background and are interested in working closely with researchers and other engineers Enjoy pair programming (we love to pair!) Care about code quality, testing, and More ❯

from day one. Youll need to be both a scientist and an engineer: excited by innovation, and pragmatic about delivering impact! Python and modern ML libraries (e.g. PyTorch, TensorFlow, JAX) AWS and cloud infrastructure for scalable training and inference ML ops tooling, model monitoring, and data pipelines Bonus: experience with LLMs & generative AI is a strong plus What Theyre Looking More ❯

workflow orchestration tools (e.g., Kubeflow, Ray, Airflow, Metaflow). Excellent programming skills in Python; experience with Bash, Go, or C++ is beneficial. Strong understanding of ML frameworks (PyTorch, TensorFlow, JAX) and familiarity with distributed training methods, GPU acceleration, and optimization libraries (e.g., XLA, NCCL). Excellent understanding of software development best practices, CI/CD, and automation. Familiarity with GPU More ❯

problems. (Desirable) Experience designing and conducting experiments in a social science or human-computer interaction (HCI) context. Strong proficiency in Python and common ML libraries/frameworks (e.g., PyTorch, JAX, TensorFlow, Hugging Face). (Desirable) A track record of publications in relevant AI or interdisciplinary conferences. A strong scientific mindset geared towards rigorous experimentation, coupled with the engineering discipline to More ❯

and requirements for an end-to-end stack; Experience MS, or higher degree, in a related field, or equivalent industry experience Professional experience with ML frameworks such as PyTorch, Jax or Tensorflow (PyTorch preferred) Experience with data sampling and data curation pipelines for autonomous driving datasets Experience in state-of-the-art architectures for end-to-end autonomous driving Experience More ❯

and requirements for an end-to-end stack; Experience MS, or higher degree, in a related field, or equivalent industry experience Professional experience with ML frameworks such as PyTorch, Jax or Tensorflow (PyTorch preferred) Experience with data sampling and data curation pipelines for autonomous driving datasets Experience in state-of-the-art architectures for end-to-end autonomous driving Experience More ❯

and requirements for an end-to-end stack; Experience MS, or higher degree, in a related field, or equivalent industry experience Professional experience with ML frameworks such as PyTorch, Jax or Tensorflow (PyTorch preferred) Experience with data sampling and data curation pipelines for autonomous driving datasets Experience in state-of-the-art architectures for end-to-end autonomous driving Experience More ❯

or a related field, plus 3+ years of relevant experience. Demonstrated expertise applying deep learning to omics data at scale. Proficiency in Python and modern deep learning frameworks (PyTorch, JAX, or similar). Experience designing and operating data pipelines for genomics, transcriptomics, proteomics, or metabolomics. Solid grasp of causal inference, experimental design, and statistics. Familiarity with software engineering best practices More ❯

on distributed training infrastructures. Familiarity with evaluating and improving the generalizability and robustness of ML systems. Proficiency in programming languages such as Python and ML frameworks (e.g., PyTorch, TensorFlow, JAX). Excellent communication skills to collaborate effectively with cross-functional teams and present findings. One or more papers at top-tier venues (such as NeurIPS, ICML, ICLR, AIStats, MLSys, JMLR More ❯

tools, and hardware optimisation techniques Experience with distributed training frameworks (Ray, Dask, PyTorch Lightning, etc.) Expertise with Python and/or C/C++ Development with machine learning frameworks (JAX, Tensorflow, PyTorch etc.) Passion for profiling, identifying bottlenecks, and delivering efficient solutions. Highly Desirable Track record of successfully scaling ML models. Experience writing custom CUDA kernels or XLA operations. Understanding More ❯

GPU architectures (NVIDIA) - experience with Qualcomm is a must Experience with state-of-the-art performance toolkits, software stacks and profiling tools (Cuda/CuDNN/TensorRT, Jit + Jax) Proficient knowledge of Python, C/C++, PyTorch, TensorFlow, Keras Fundamental knowledge of ARM/x86 assembly Fundamental knowledge about parameter efficient fine-tuning techniques (e.g., LoRA, PEFT) Good written More ❯

supervised pre training, Vision Transformers, or vector quantization methods. Hands on work with large medical or scientific imaging datasets and establishing evaluation tasks and metrics. Proficiency in PyTorch or JAX and experience running distributed training on GPUs or cloud HPC resources. Strong software engineering habits: version control, testing, continuous integration, code review, and containerization. Clear communication and ability to work More ❯

track record of successfully implementing and deploying AI models in production environments. Proficiency in programming languages such as Python, C++ and deep expertise with frameworks such as PyTorch/Jax Strong understanding of deep learning fundamentals, including neural network architectures, optimization techniques, and evaluation metrics. Experience in distributed training and inference of large scale AI models on thousands of GPUs More ❯

overall business objectives. You may be a good fit if you have: Extremely strong software engineering skills. Proficiency in Python and related ML frameworks such as Tensorflow, TF-Serving, JAX, and XLA/MLIR. Deep experience in building and leading a product-centric organisation. Direct experience working as part of a team building Large Language Models. Released multiple features with More ❯

multidisciplinary environment Familiarity with modern distributed big data tools and pipelines such as Apache Spark, Arrow, Airflow, Delta Lake, or similar Familiarity with machine learning frameworks like PyTorch or JAX In-depth experience with cloud computing resources Thorough knowledge of GPU-based HPCs in the context of machine learning. EDUCATION & EXPERIENCE (REQUIRED): Bachelor's degree and three years of relevant More ❯

proficient software engineer in a least one programming language (Python or other e.g. Rust, Go, Java) • You have, hands-on experience with AI frameworks and tools (e.g., TensorFlow, PyTorch, Jax) • You have high technical engineering competence. This means being able to design complex software and make it usable in production • You have a high scientific track record in a field More ❯

ideally including transformers, diffusion models, or multimodal architectures. Experience applying ML to large multimodal biological datasets (genomics, transcriptomics, epigenomics, proteomics, single-cell data). Exceptional coding skills (Python, PyTorch, JAX, TensorFlow) and familiarity with scalable training frameworks. Experience managing large-scale distributed training across GPUs/TPUs. Background in generative AI, large language models, mechanistic interpretability, or reinforcement learning. Interview More ❯