22 of 22 Google JAX Jobs

Strong software engineering skills: clean code, testing, debugging, version control, and system design. Proficiency in Python with experience in ML frameworks (PyTorch, TensorFlow, or JAX). Hands‐on experience with cloud platforms (AWS, GCP, or Azure) and containerisation (Docker, Kubernetes). Solid understanding of ML fundamentals (model training, evaluation ...

equivalent experience in Computer Science, Maths, Machine Learning, Data Science, or related field. Desirable: Exposure to machine learning frameworks such as PyTorch, JAX, Triton, TensorFlow Experience with distributed workload management systems such as Kubernetes, VLLM, Keras or MLOps pipelines Experience working with hardware simulators or emulators (e.g. QEMU). ...

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) Experience influencing organizational policy and securing major research funding ...

have been instrumental in: building machine learning models and pipelines in Python, using common libraries and frameworks (PyTorch/CUDA, ideally with exposure to JAX, NumPy/SciPy), especially including deep learning applications; developing models for bespoke problem settings that involve high‐dimensional data (spatiotemporal, geometric, physical); iterating ...

related technical field, with relevant industry experience in ML Engineering or Applied Research. Advanced proficiency in Python and modern deep learning ecosystems (PyTorch, JAX, Hugging Face). Strong ability to interpret unstructured model outputs (text, transcripts, embedding spaces) and synthesize qualitative findings into actionable engineering guidance and training objectives. ...

machine learning models for time-series or sensor data Strong programming skills in Python Experience with machine learning frameworks such as PyTorch, TensorFlow, or JAX Experience building data pipelines and training workflows Ability to work with imperfect, noisy, or incomplete datasets Nice to Have Experience with physiological signal processing ...

ICLR. Hands-on experience applying deep learning models to complex, ideally temporal or financial, datasets. Expertise in Python and modern ML frameworks (TensorFlow, PyTorch, JAX, etc.). Prior experience in a commercial or industry setting post-PhD, ideally in a similarly data-driven domain. Why Apply Compensation and total ...

reinforcement learning Experience with agent frameworks, tool-use planning and workflow orchestration Systems-level fluency across data pipelines, training infrastructure and inference (PyTorch, JAX, TensorFlow) Strong MLOps discipline: CI/CD for models, offline/online evaluation, safety and guardrails The ability to influence at exec level and mentor ...

particularly in the field of deep learning very strong programming skills in Python experience with at least one deep learning framework (e.g., PyTorch or JAX) strong background in computer vision and probabilistic modeling knowledge of representation learning, self supervised learning, or transfer learning interest in digital signal processing, physics ...

members in diverse fields Strong programming abilities in Python, and extensive experience with the scientific and machine-learning stack: Numpy, Torch/Tensorflow/Jax, Scikit-learn, Polars, SQL Expertise with deep learning approaches such as diffusion or flow matching Proficiency in modern software development practices: code testing, documentation ...

knowledge of ML evaluation, validation strategy, and failure modes including error analysis and iteration planning ● Experience with model development using PyTorch/TensorFlow/JAX ● Ability to communicate clearly across technical + scientific stakeholders ● Strong experience leading or coordinating cross-functional teams, and thinking strategically across product and science ...

work in bwHPC-S5. Ideally, your profile is supplemented by: Experience with AI frameworks, workloads (e.g. Natural Language Processing), and libraries (e.g., PyTorch or JAX). Experience with parallel programming paradigms. Some background in the field of (green) transport (e.g., fleet optimisation, energy-efficient logistics, smart city planning). ...

3. A working knowledge and practical experience with Python, and extensive experience with the scientific and machine-learning stack: Numpy, Torch/Tensorflow/Jax, Scikit-learn, Polars, SQL. Key Words: Machine Learning Engineer/Data Processing/Model Building/NMR/Deep Learning/Computational Biophysics/ ...

Hands‐on experience training, fine‐tuning, or deploying large‐scale ML models in production. Proficiency with at least one modern ML framework (e.g. PyTorch, JAX), and ability to learn others quickly. Experience with distributed training and inference frameworks (e.g. DeepSpeed, FSDP, Megatron, ZeRO, Ray). Strong software engineering fundamentals ...

work with minimal friction. Iterations on models and systems are measurable, safe, and improve user experience over time. Tech Stack Python PyTorch/JAX GPU-based training and inference system Ideal Experience You have built or shipped real ML systems used by people, not just demos. You are comfortable ...

software engineering practices* Demonstrated expertise in building production-quality code and data pipelines for ML systems* Proficiency in modern AI development frameworks including: PyTorch, Jax , HuggingFace Transformers, LLM APIs (litellm etc) and vLLM for building and deploying large-scale AI applications* Understanding of LLM training methodologies including instruction fine … generation, data curation, or curriculum learning pipelines* Experience training large-scale models over distributed nodes with cloud tools such as AWS, MS Azure, or Google Cloud* Hands-on experience with MLOps, experiment tracking, and model deployment systems* Strong interest in staying current with ML research literature and ability ...

About Graphcore At Graphcore, we’re building the future of AI compute.We’re a team of semiconductor, software and AI experts, with deep experience in creating the complete AI compute stack - from silicon and software ...

researchers and contribute to a culture of technical excellence. Must-Have Skills: Machine Learning, Deep Learning, NLP, Computer Vision, Generative AI, Python, TensorFlow, PyTorch, JAX Other Skills: Machine Learning, Deep Learning, NLP, Computer Vision, Generative AI, Python, TensorFlow, PyTorch, JAX Apply Here Click here to apply ...

AI Scientist/Machine Learning Engineer We are looking for an AI scientist or machine learning engineer to design and implement the algorithms that power Biostream’s physiological monitoring and alert systems. You will work ...

intuitive OS and interfaces for orchestrating factories, monitoring machines, controlling production, etc. all with AI. For context, we are a small dynamic team from Google X, Microsoft, Cambridge, MIT, Imperial, BBC R&D to name a few. We work a lot and are all close friends – come join … machine learning mage: You write clean, scalable, high-performance deep learning code. You take pride in your craft. Proficiency in PyTorch, Tensorflow, Jax, or equivalent is a must (ideally PyTorch). Knowledge on some of the latest good stuff from transformers to VLMs and NERFs. Happy to get down ...

World Wide Technology UK is looking for a hands-on Cloud Engineer with strong expertise in HPC and AI/ML performance workloads on Google Cloud Platform (GCP). The role focuses on benchmarking, optimizing, and validating performance across advanced accelerator platforms including NVIDIA GPUs, AMD GPUs, and Google … inference, scientific workloads) Provision and optimize GPU/TPU-based infrastructure on GCP (A3/A4, TPU pods) Analyze performance across frameworks (PyTorch, TensorFlow, JAX, CUDA, ROCm) Identify system bottlenecks (compute, memory, network, I/O) Build automation tools for benchmarking and reporting Collaborate with teams to align workloads ...

Bjak is seeking a Technical Lead in Machine Learning to oversee the execution layer of their AI chat app. This role involves managing ML systems, ensuring they are trainable and deployable under real-world constraints. ...