26 to 50 of 60 PyTorch Jobs in the South East

scope projects, test prototypes, and deliver operational improvements. Document solutions and provide light training/support to business users. What We're Looking For: Strong programming skills in Python (PyTorch, Hugging Face, scikit-learn). Experience with fine-tuning/adapting pre-trained AI models . Solid data handling skills (SQL, Pandas, preprocessing for text, audio, or images). Familiarity More ❯

relevant discipline. Strong background in Machine Learning and/or statistical signal processing applied to sequential/sensor data. Proficiency in Python with experience in frameworks such as TensorFlow, PyTorch, or scikit-learn. Demonstrated expertise in developing ML solutions for real-world problems. Desirable Experience (one or more areas): RF communications, radar, sonar, or electronic warfare. Tracking, sensor data fusion More ❯

. Proficiency in containerization and orchestration (Docker, Kubernetes). Expertise in managing and optimizing cloud-based systems at scale. Preferred Skills Familiarity with Python (Jupyter) and ML frameworks (e.g., PyTorch). Knowledge of monitoring tools (Prometheus, Grafana). Experience with cloud-based databases (RDS, Aurora, Redshift, Cloud SQL, etc.) and visualization tools (QuickSight, Superset). Understanding of CI/CD More ❯

Calibratin 3D stere, SLAM or Depth estimation from video Proficient in Linux Experience with Docker Experience with large-scale data sets Proficient with open source machine learning platforms such PyTorch or Keras/tensorflow. Ability to develop using rapid prototyping techniques aimed at demonstrating applications quickly in a fast moving environment. Agile/DevOps Familiarity f SCRUM Familiarity f DevOps More ❯

AI technologies, algorithms, and frameworks . Proficiency in programming languages (Python, R, C/C++, Java) and secure coding practices. Hands-on experience with ML/LLM frameworks (TensorFlow, PyTorch, scikit-learn, etc.). Expertise in DevOps/CI/CD security and cloud-native architectures (containers, Kubernetes, Git). Strong knowledge of AI/ML-specific security vulnerabilities (adversarial More ❯

Start-up/Scale-up Experience Strong cloud skills (AWS, GCP, Azure) and containerisation (Docker, Kubernetes) Experience in automating deployments and orchestrating cloud environments Nice to have: Python (Jupyter, PyTorch), monitoring tools (Prometheus, Grafana), cloud databases (RDS, Aurora, Spanner), CI/CD tools (CircleCI), and data visualisation experience. This is a unique opportunity to join a visionary team redefining AI More ❯

etc.) for automation. Hands-on experience with containerization & orchestration (Docker, Kubernetes, Terraform). Skilled in cloud platforms (AWS, GCP, or Azure). Bonus points for: Familiarity with ML frameworks (PyTorch, Jupyter). Knowledge of cloud monitoring tools (Prometheus, Grafana). Experience with cloud-based databases (RDS, Aurora, Redshift, Spanner, etc.). Exposure to CI/CD pipelines (e.g., CircleCI). More ❯

such as stratigraphy, sedimentology, or petroleum geology. Experience of working with subsurface datasets (e.g., wireline, seismic, biostratigraphy). Strong python programming skills and experience with ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). Excellent communication and teamwork skills in a collaborative R&D environment. AI/ML Implementation: Design and implement AI/ML algorithms to automate and enhance geological More ❯

complex real-world problems across domains such as computer vision, natural language processing, and time-series analysis. Key Responsibilities: Design and implement deep learning models using frameworks such as PyTorch or TensorFlow. Collaborate with data scientists, ML engineers, and product teams to define model requirements and deployment strategies. Optimize model performance and scalability for production environments. Conduct experiments, evaluate model … research and techniques in deep learning. Required Skills & Experience: Proven experience in developing and deploying deep learning models in production. Strong proficiency in Python and deep learning libraries (e.g., PyTorch, TensorFlow, Keras). Solid understanding of neural network architectures (CNNs, RNNs, Transformers, etc.). Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Familiarity with MLOps More ❯

complex real-world problems across domains such as computer vision, natural language processing, and time-series analysis. Key Responsibilities: Design and implement deep learning models using frameworks such as PyTorch or TensorFlow. Collaborate with data scientists, ML engineers, and product teams to define model requirements and deployment strategies. Optimize model performance and scalability for production environments. Conduct experiments, evaluate model … research and techniques in deep learning. Required Skills & Experience: Proven experience in developing and deploying deep learning models in production. Strong proficiency in Python and deep learning libraries (e.g., PyTorch, TensorFlow, Keras). Solid understanding of neural network architectures (CNNs, RNNs, Transformers, etc.). Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Familiarity with MLOps More ❯

complex real-world problems across domains such as computer vision, natural language processing, and time-series analysis. Key Responsibilities: Design and implement deep learning models using frameworks such as PyTorch or TensorFlow. Collaborate with data scientists, ML engineers, and product teams to define model requirements and deployment strategies. Optimize model performance and scalability for production environments. Conduct experiments, evaluate model … research and techniques in deep learning. Required Skills & Experience: Proven experience in developing and deploying deep learning models in production. Strong proficiency in Python and deep learning libraries (e.g., PyTorch, TensorFlow, Keras). Solid understanding of neural network architectures (CNNs, RNNs, Transformers, etc.). Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Familiarity with MLOps More ❯

production-scale AI systems. Expertise in Agentic AI, LLM-based architectures, NLP techniques, and generative AI models. Solid programming skills (Python preferred) and experience with ML frameworks such as PyTorch, TensorFlow, Hugging Face. Hands-on experience with prompt engineering, fine-tuning LLMs, and building multi-agent systems. Comfortable balancing strategic thinking with hands-on coding. If you want to lead More ❯

production-scale AI systems. Expertise in Agentic AI, LLM-based architectures, NLP techniques, and generative AI models. Solid programming skills (Python preferred) and experience with ML frameworks such as PyTorch, TensorFlow, Hugging Face. Hands-on experience with prompt engineering, fine-tuning LLMs, and building multi-agent systems. Comfortable balancing strategic thinking with hands-on coding. The client is accepting candidates More ❯

fine-tuning, prompt engineering and productionisation · Deep experience in MLOps on Azure, including CI/CD, monitoring and scaling pipelines. · Strong coding skills in Python, with frameworks such as PyTorch, FastAPI and Azure CLI. ALL APPLICANTS MUST BE FREE TO WORK IN THE UK Exposed Solutions is acting as an employment agency to this client. Please note that no terminology More ❯

GANs, Diffusion Models). Strong understanding of financial use cases: fraud detection, algorithmic trading, regulatory tech, and personalisation. Experience with cloud-native AI platforms (Azure, AWS, GCP) and frameworks (PyTorch, TensorFlow). Exceptional stakeholder management and communication skills. Track record of building and scaling high-performing AI teams. This role is an urgent requirement, there are limited interview slots left More ❯

Good programming ability in Python with familiarity with Linux systems including scripting and system configuration. Experience using AWS, e.g, Cognito, S3, EC2, Lamdas, etc. Experience with ML toolkits, e.g. PyTorch, Lightning, etc., along with a solid understanding of how these fit into ML Ops pipelines and tools. Be able to design and implement MLOps solutions covering many different technologies. Desirable More ❯

inference endpoints. Support pre-sales efforts, workshops, and proof-of-concepts alongside go-to-market teams. AI & ML Engineering Implement and optimise AI/ML models using frameworks like PyTorch, HuggingFace, LangChain, and NVIDIA Triton. Fine-tune foundation models for domain-specific use cases. Deploy and maintain inference services using REST/gRPC APIs, containerised and distributed systems. Data & Knowledge More ❯

inference endpoints. Support pre-sales efforts, workshops, and proof-of-concepts alongside go-to-market teams. AI & ML Engineering Implement and optimise AI/ML models using frameworks like PyTorch, HuggingFace, LangChain, and NVIDIA Triton. Fine-tune foundation models for domain-specific use cases. Deploy and maintain inference services using REST/gRPC APIs, containerised and distributed systems. Data & Knowledge More ❯

inference endpoints. Support pre-sales efforts, workshops, and proof-of-concepts alongside go-to-market teams. AI & ML Engineering Implement and optimise AI/ML models using frameworks like PyTorch, HuggingFace, LangChain, and NVIDIA Triton. Fine-tune foundation models for domain-specific use cases. Deploy and maintain inference services using REST/gRPC APIs, containerised and distributed systems. Data & Knowledge More ❯

with some C++). Experience in embedded systems and automation/control mechanisms. Track record of leading or mentoring software engineers. Exposure to AWS and AI/ML frameworks (PyTorch, TensorFlow, OpenCV) is a big plus. Flexible, solutions-focused mindset – comfortable in a start-up environment. Nice-to-haves: Microcontrollers (Raspberry Pi, Okdo, Tinker Edge R). Robotics, servo/ More ❯

finance experts to translate real-world workflows into AI agents. Key Requirements: Strong experience in NLP/LLM training and fine-tuning (transformers, embeddings, LoRA/PEFT).Proficiency with PyTorch/TensorFlow, Hugging Face ecosystem, and MLOps tooling. Experience working with financial or structured transactional data. Knowledge of data privacy and regulatory requirements in fintech (SOC2, PCI-DSS, GDPR). More ❯

object shape, appearance and movement. • Excellent team working abilities with positive, can-do attitude. • Examples of working with large spatio-temporal datasets. • Experience with Python and ML toolkits, e.g. PyTorch, Lightning, etc. Desirable Skills • Relevant conference, journal, or other peer-reviewed output. • Experience delivering the full ML development lifecycle, taking systems from research prototypes through to development and production within More ❯

systems Build tooling for deployment, monitoring, and continuous improvement of AI models What We're Looking For: Strong programming skills (Python, C++, or similar) Experience with ML frameworks (e.g. PyTorch, TensorFlow, JAX) Familiarity with cloud infrastructure and distributed systems Solid understanding of performance optimization and system design More ❯

systems Build tooling for deployment, monitoring, and continuous improvement of AI models What We're Looking For: Strong programming skills (Python, C++, or similar) Experience with ML frameworks (e.g. PyTorch, TensorFlow, JAX) Familiarity with cloud infrastructure and distributed systems Solid understanding of performance optimization and system design More ❯

deliver transformative, compliant, and ethical AI solutions. Requirements: Proven experience leading AI initiatives in banking, capital markets, or insurance. Deep technical expertise in generative AI technologies and frameworks (e.g., PyTorch, TensorFlow, Hugging Face). Strong business acumen and ability to align AI with client goals. Excellent leadership, communication, and stakeholder management skills. Passion for innovation and staying ahead of AI More ❯