176 to 200 of 396 Permanent PyTorch Jobs

developing and deploying perception algorithms (e.g., object detection, segmentation, tracking, SLAM, multi-sensor fusion) in real-world applications Proficiency in Python and C++ Experience with deep learning frameworks (e.g., PyTorch, TensorFlow) and MLOps tools/platforms Communication, interpersonal, and collaboration skills for working in a dynamic, cross-functional environment Company Statements Equal Opportunity Rivian is an equal opportunity employer and More ❯

Collaborate with data and software engineers to deliver integrated solutions. Degree in Computer Science, Engineering, or a related field. Hands-on experience with AI technologies and frameworks (e.g., TensorFlow, PyTorch). Proficiency in programming languages such as Python, Java, or C#. Experience with API design and management, as well as data integration techniques. Strong experience of setup of cloud services More ❯

ability to collaborate effectively across departments Strong project management and organisational skills Proficiency in programming languages such as Python, Java, or Scala, and experience with ML frameworks like TensorFlow, PyTorch, or scikit-learn Experience with large-scale distributed systems and big data technologies (e.g., Spark, Hadoop, Kafka) Accommodation requests If you need assistance with any part of the application or More ❯

current with emerging techniques. You are experienced in multivariate testing, mentoring junior scientists, and leading technical decisions. You are proficient in Python, Java, Scala, and ML frameworks (e.g., TensorFlow, PyTorch), with experience in cloud platforms (AWS), big data (Spark), and deployment tools (Kubernetes, Airflow, Docker). Accommodation requests If you need assistance with any part of the application or recruiting More ❯

building features which deliver AI capabilities to some of the biggest names in the insurance industry. We are developing a modern real-time ML platform using technologies like Python, PyTorch, Ray, k8s (helm + flux), Terraform, Postgres and Flink on AWS. We are very big fans of Infrastructure-as-Code and enjoy Agile practices. As a team, we're driven More ❯

a relevant discipline Strong background in AI/ML and/or statistical signal processing applied to time-series or sequential data Proficiency in Python with experience using TensorFlow, PyTorch, scikit-learn, or similar ML frameworks Experience leading R&D projects and mentoring early-career researchers Ability to work independently or within collaborative team Reference: AMC/DRI/RS2 More ❯

record leading technical teams and securing research funding Strong background in areas like NLP, computer vision, graph ML, or signal processing Skilled in Python and familiar with frameworks like PyTorch or TensorFlow Experience with engineering assurance and proposal writing (e.g. Dstl, EPSRC) This is a unique opportunity to influence high-impact innovation in a multi-disciplinary, research-driven environment. Reference More ❯

record leading technical teams and securing research funding Strong background in areas like NLP, computer vision, graph ML, or signal processing Skilled in Python and familiar with frameworks like PyTorch or TensorFlow Experience with engineering assurance and proposal writing (e.g. Dstl, EPSRC) This is a unique opportunity to influence high-impact innovation in a multi-disciplinary, research-driven environment. Reference More ❯

solutions Publish research and engage with academic partners What You'll Bring: PhD or equivalent experience in AI/ML or signal processing Proficiency in Python and ML frameworks (PyTorch, TensorFlow, scikit-learn) Strong experience with time-series data, decision-making models, or sensor fusion A track record of innovation and delivering complex R&D Preferred Expertise: RF comms, radar More ❯

if, and surprise us again, and again. Proven track record delivering impactful ML/AI solutions in production. Deep expertise in Python and modern AI/ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn, NumPy, Pandas). Hands-on experience with GenAI, agentic AI, and automated testing for AI systems. Curiosity and creativity to challenge assumptions and explore new approaches. Strong More ❯

PhD experience applying AI/ML and/or statistical signal processing to sequential or time-series data Strong Python development skills with experience in ML libraries (e.g., TensorFlow, PyTorch, scikit-learn) Ability to lead and deliver research programmes independently and in teams Desirable Experience (one or more of the following): RF communications or electronic warfare (EW) Radar or acoustic More ❯

series or physiological data. Strong foundation in signal processing and time-series modeling (e.g., deep learning, classical ML, anomaly detection). Proficient in Python and ML frameworks such as PyTorch or TensorFlow. Familiarity with FDA regulatory pathways for medical software (e.g., 510(k), De Novo), and standards like IEC 62304 or ISO 13485. Experience with MLOps practices and model versioning More ❯

LLMs in real-world or defence-related contexts Graph-structured data and graph algorithms Designing and utilising relational or graph databases Desirable Experience: Experience with graph ML libraries (e.g., PyTorch-Geometric, PyKeen) or KG tools (e.g., Neo4j) Familiarity with query languages such as SQL or Cypher Understanding of semantic reasoning, ontology design, or knowledge representation Why Apply? Work on high More ❯

statistical analysis and proven experience applying a range of machine learning techniques to solve business problems (e.g., regression, classification, clustering, time-series forecasting). Practical experience with Keras or PyTorch is required. Full-Stack Deployment: Demonstrable experience taking models to production, including building and deploying APIs with FastAPI and using Vertex AI for ML workflows. Visualization & Communication: Ability to create More ❯

or custom tools). Strong understanding of computer architecture fundamentals : memory systems, interconnects, queuing theory, Amdahl's and Gustafson's laws. Familiarity with machine learning workloads and frameworks like PyTorch, TensorFlow, or JAX. Ability to interpret RTL/schematics and discuss micro-architectural trade-offs with hardware engineers. Excellent data visualization and communication skills - capable of distilling millions of simulation More ❯

or custom tools). Strong understanding of computer architecture fundamentals : memory systems, interconnects, queuing theory, Amdahl's and Gustafson's laws. Familiarity with machine learning workloads and frameworks like PyTorch, TensorFlow, or JAX. Ability to interpret RTL/schematics and discuss micro-architectural trade-offs with hardware engineers. Excellent data visualization and communication skills — capable of distilling millions of simulation More ❯

or custom tools). Strong understanding of computer architecture fundamentals : memory systems, interconnects, queuing theory, Amdahl's and Gustafson's laws. Familiarity with machine learning workloads and frameworks like PyTorch, TensorFlow, or JAX. Ability to interpret RTL/schematics and discuss micro-architectural trade-offs with hardware engineers. Excellent data visualization and communication skills — capable of distilling millions of simulation More ❯

Neocloud space. Practical knowledge of AI/ML technologies and their applications, including understanding language models (LLMs), and experience with training and fine-tuning LLMs using frameworks like TensorFlow, PyTorch, or Hugging Face Transformers. Good understanding of programming/scripting: (e.g., Python, Go) for customizing solutions, creating scripts, or automating tasks. Experience with AI relevant infrastructure, including Networking (InfiniBand and More ❯

facing product 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 More ❯

state-of-the-art models for a variety of computer vision tasks, including detection, segmentation, and classification. Writing highly efficient, scalable, and production-ready code in Python using the PyTorch framework. Optimizing models for high-performance inference on diverse hardware using tools like NVIDIA TensorRT, OpenVINO, and ONNX. Managing and processing large-scale datasets and implementing advanced data augmentation strategies. More ❯

state-of-the-art models for a variety of computer vision tasks, including detection, segmentation, and classification. Writing highly efficient, scalable, and production-ready code in Python using the PyTorch framework. Optimizing models for high-performance inference on diverse hardware using tools like NVIDIA TensorRT, OpenVINO, and ONNX. Managing and processing large-scale datasets and implementing advanced data augmentation strategies. More ❯

a rough guide): Understanding of and interest in the full machine learning lifecycle, including deploying trained machine learning models developed using common frameworks such as Scikit-learn, TensorFlow, or PyTorch Understanding of the core concepts of probability and statistics and familiarity with common supervised and unsupervised learning techniques Experience in Software Engineering including programming in Python. Technical experience of cloud More ❯

business settings. Skills in prompt engineering, RAG, guardrail design, orchestration, and tools like LangGraph or Semantic Kernel. Deep knowledge of ML model development, deployment, and evaluation. Proficiency in Python, PyTorch, TensorFlow, SQL, Spark, and AWS tools like SageMaker and Bedrock. Understanding of scalable data infrastructure and cloud architecture. Location & Relocation: This role is based in Sydney, Australia . We offer More ❯

Master's, PhD or equivalent experience in a technical field (e.g., Maths, Statistics, Computer Science, Physics, Chemistry, Biomedical Engineering). Python programming in a modern deep learning framework, e.g. PyTorch or JAX. Familiar with deep learning fundamentals: models, optimisation, evaluation and scaling. Capable of designing, executing and reporting from ML experiments. Mathematics skills to support the above: calculus, probability theory More ❯

field. Strong familiarity with Linux and the open-source ecosystem. Proficient experience working with machine learning and large datasets. In-depth understanding of open source machine learning frameworks (e.g., PyTorch, ggml, llama.cpp, vllm). Experience building complex systems on the cloud. Experience building and optimizing distributed systems and large-data applications, including those using tensor accelerators or GPUs. Strong analytical More ❯