10 of 10 PyTorch Jobs in South London

clear communication skills Nice To Have: Prior exposure with execution algos, TCA, order-routing, or market-impact modelling Knowledge of statistical or machine-learning libraries (NumPy, pandas, scikit-learn, PyTorch) Experience building distributed systems with message buses (Kafka, ZeroMQ) and asynchronous I/O Experience with cloud or on-prem orchestration and scheduling frameworks (Kubernetes, HT Condor, SLURM) Benefits Tower More ❯

You have strong foundational software engineering knowledge, including data structures, algorithms, system design, and OOP. You have advanced knowledge of LLM architectures and ML/DL frameworks (e.g., TensorFlow, PyTorch, LangChain, Keras, scikit-learn). You're ready to design, deploy, and maintain production-grade Machine Learning systems. You're willing to champion best practices in code quality, testing, observability More ❯

Scientist 's working across a variety of companies & industries Provide hands-on coding sessions and real-world project mentorship using Python and relevant ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch etc) Incorporate cloud-based tools and services (e.g., AWS, GCP, or Azure) into training to simulate modern ML engineering environments (Cloud Training can be provided to you) Keep training material More ❯

Scientist 's working across a variety of companies & industries Provide hands-on coding sessions and real-world project mentorship using Python and relevant ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch etc) Incorporate cloud-based tools and services (e.g., AWS, GCP, or Azure) into training to simulate modern ML engineering environments (Cloud Training can be provided to you) Keep training material More ❯

with 4+ years of relevant industry experience. Strong expertise in deep learning, neural networks, and generative models (GANs, diffusion models). Practical experience with modern machine learning frameworks (e.g., PyTorch, TensorFlow). Advanced programming skills in Python . Strong problem-solving, analytical, and communication skills. Demonstrated ability to work effectively in multidisciplinary, fast-paced, research-driven teams. Preferred Qualifications Experience More ❯

degree (or equivalent) in Computer Science, Machine Learning, or a related field. 3+ years of experience deploying ML models in production. Proficient in Python and ML frameworks (e.g., TensorFlow, PyTorch). Experience working with cloud platforms and containerised deployments (e.g., Docker, Kubernetes). Solid grounding in computer vision and experience with large-scale data. Bonus: exposure to reinforcement learning methods. More ❯

on AI trends and contribute to open research Requirements: PhD or equivalent experience in ML, AI, CS, physics, or mathematics Proficient in Python, C++, and deep learning frameworks (e.g., PyTorch, TensorFlow) Solid grasp of ML techniques; independent and team-oriented mindse Preferred: Experience in LLMs, reinforcement learning, or chip design Familiarity with JAX and optimization frameworks Why Join Us: Work More ❯

in LLMs and Algorithms Experience with data preprocessing and feature extraction Proficiency in programming languages like Python or R (4+ years) Knowledge of machine learning frameworks like TensorFlow or PyTorch Excellent problem-solving and analytical skills What you don't know, we can teach - as long as you have the desire to learn. We are a group of serious engineers More ❯

term pain for extreme long-term pain. Embrace an extreme learning rate rather than assuming limits to your ability/knowledge. Responsibilities: Lower deep learning graphs—from common frameworks (PyTorch, TensorFlow, Keras, etc.) down to an IR representation for training—with particular focus on ensuring reproducibility. Write novel algorithms for transforming intermediate representations of compute graphs between different operator representations. … modular software design. Deep Learning understanding—both in terms of recent architecture trends + fundamentals of how training works, and experience with machine learning frameworks and their internals (e.g., PyTorch, TensorFlow, scikit-learn, etc.). Exposure to Deep Learning Compiler frameworks—e.g., TVM, MLIR, TensorComprehensions, Triton, JAX. Kernel Experience—experience writing and optimizing highly-performant GPU kernels. Note: For potential More ❯

Reinforcement Learning (or equivalent hands-on experience). Deep understanding of robot manipulation—both classical and ML-based approaches. Proficiency in Python & C++, and experience with ML frameworks like PyTorch or TensorFlow. Strong grasp of real-world robotic constraints and embedded systems. Excellent communication and a collaborative mindset. ? Bonus Points For Experience deploying robotic systems in real-world environments. Knowledge More ❯