7 of 7 Transfer Learning Jobs in England

PDE) Team to deliver first class coaching and training for our Level 6 AI Engineer programme. To be successful in this role you must possesses practical expertise in machine learning, with experience across the full lifecyclefrom business scoping and data engineering through to deployment, monitoring, and ethical considerations. Familiar with classical ML techniques (e.g., regression, classification, clustering), as well … as deep learning, NLP, transfer learning, and recent advancements in LLMs and generative AI. Able to contextualise these techniques in industry settings, such as financial forecasting, operations optimisation, or customer segmentation. Comfortable with key ML frameworks (such as Scikit-learn, TensorFlow, PyTorch, Hugging Face) and data manipulation tools (Pandas, NumPy), as well as version control, containerisation, and … help others succeed. Personality and Attitude A self-starter and self-manager who can engage people, keep them engaged and progressing through the qualification. Want to teach and ensure learning is taking place. A can-do and upbeat attitude to work, colleagues, clients and managers. An inquisitive mind, able to find things out and problem solve. Solutions focused with More ❯

Skills: Statistics and data science algorithms Programming: Proficiency in Python and AI/ML libraries NLP: Expertise in tools like TensorFlow, spaCy, NLTK Data Management: Preprocessing, cleaning, and transformation Transfer Learning: Refining pre-trained LLMs for specific needs Analytics: strong foundation in mathematics and data mining Familiarity with Cloud formation and AWS Stack are preferred Company Description Syngenta … Flexible working, dependent on role requirements Up to 31.5 days annual holiday. We offer a position which contributes to valuable and impactful work in a stimulating and international environment. Learning culture and wide range of training options. Syngenta has been ranked as a top 5 employer and number 1 in agriculture by Science Journal. More ❯

the short-term roadmap working closely with Product and Engineering and make investments for the long-term. Our research themes include, but are not limited to: foundational models, contrastive learning, diffusion models, few-shot and zero-shot learning, transfer learning, unsupervised and semi-supervised methods, active learning and semi-automated data annotation, deep learning … integrated into Alexa devices such as Echo Show. We solve real-world problems using AI while being a positive force for good. BASIC QUALIFICATIONS - 6+ years of building machine learning models for business application experience - PhD, or Master's degree and 6+ years of applied research experience - Experience programming in Java, C++, Python or related language - Experience with neural … deep learning methods and machine learning PREFERRED QUALIFICATIONS - PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field - Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc. - Experience with large scale distributed systems such as Hadoop, Spark etc. - Excellent technical publications and material More ❯

other relevant engineering domains. 1+ year of successful project management experience in leading and managing engineering teams in a technology-driven company. Strong understanding of AI technologies, including machine learning, natural language processing, or computer vision; or mathematical optimization. Experience with LLMs and Generative AI techniques such as fine tuning, pruning, RAG systems, transfer learning etc. Excellent More ❯

Product Development and Manufacturing Solutions division. The team you will join is spearheading the development of Fusion's cloud-based automation and AI-powered capabilities. As a Senior Machine Learning Engineer, you will leverage your engineering skillset and research expertise to tackle complex problems in building comprehensive AI/ML solutions. Your involvement will span from data preparation at … novel and creative approaches. Model Development: Develop ML models, building on the latest published research. Model Improvement: Improve and customize existing models using methodologies like RAG, fine-tuning, and transfer-learning. Integration: Integrate existing ML models into novel applications. Application Development: Develop and deploy applications that integrate AI/ML technology or models. Problem Solving: Apply ML methods to … best practices. Collaboration: Work collaboratively with cross-functional teams to integrate research findings into product development. Mentorship: Mentor and guide junior researchers and engineers, fostering a culture of continuous learning and improvement. Publication: Publish research findings in top-tier conferences and journals; represent Autodesk at industry and research events. Requirements Research Expertise: Proven research track record in AI/ More ❯

cutting-edge multimodal AI systems, integrating various modalities such as text, speech, and vision. Conduct research and experiments on our advanced compute infrastructure, exploring novel ideas in multimodal representation learning, transfer learning, and more. Collaborate closely with our world-class teams, learning from and contributing to their expertise in the field. You are an ideal candidate … Possess exceptional software engineering skills, with a proven track record of building robust and scalable systems. Have a strong command of Python and are well-versed in popular deep learning frameworks like JAX, PyTorch, and TensorFlow, with an understanding of their multimodal capabilities. Knowledge of distributed training strategies, especially for large-scale multimodal models. Familiarity with autoregressive models, particularly … research. Bonus: Experience in writing efficient GPU kernels using CUDA, optimising performance for multimodal tasks. This role is perfect for you if you: Have a deep passion for machine learning and its potential to impact various industries through multimodal applications. Enjoy tuning and optimising large multimodal models, and have experience building evaluations to measure their performance. Are comfortable diving More ❯

Assess the practicality and relevance of modern technologies such as machine learning, big data analytics, generative AI, multi-agent systems, and quantum computing in insurance and risk consulting. Work with diverse teams to pinpoint challenges in the industry and devise innovative solutions using these technologies. Examine intricate data sets to offer insights that aid in the strategic decision-making … business growth by engaging in client meetings, presentations, and proposals, highlighting the advantages and functionality of our technological offerings. Required Skills: Skilled in various modelling methods such as active learning, transfer learning, agent-based modelling, optimization, Bayesian inference, entity extraction/resolution, and spatio-temporal modelling. Proficient in developing models from fundamental principles and selecting modelling techniques More ❯