126 to 150 of 422 Permanent PyTorch Jobs

s perform common image preprocessing such as chipping, augment, or conversion using common libraries like Boto3 and NumPy. • Demonstrated professional or academic experience with deep learning frameworks such as PyTorch or Tensorflow to optimize convolutional neural networks (CNN) such as ResNet or U-Net for object detection or segmentation tasks using satellite imagery. • Demonstrated professional or academic experience with version More ❯

solutions. Strong engineering fundamentals, including DevOps, CI/CD, and secure ML/AI pipelines (DevSecOps). Highly proficient in Python, SQL, and key AI/ML frameworks (e.g., PyTorch, TensorFlow). Ability to mitigate model hallucination, optimise performance, and lead governance around AI risk and ethical deployment. Ready to Transform the Future? This a career-defining opportunity working within More ❯

solutions. Strong engineering fundamentals, including DevOps, CI/CD, and secure ML/AI pipelines (DevSecOps). Highly proficient in Python, SQL, and key AI/ML frameworks (e.g., PyTorch, TensorFlow). Ability to mitigate model hallucination, optimise performance, and lead governance around AI risk and ethical deployment. Ready to Transform the Future? This a career-defining opportunity working within More ❯

solutions. Strong engineering fundamentals, including DevOps, CI/CD, and secure ML/AI pipelines (DevSecOps). Highly proficient in Python, SQL, and key AI/ML frameworks (e.g., PyTorch, TensorFlow). Ability to mitigate model hallucination, optimise performance, and lead governance around AI risk and ethical deployment. Ready to Transform the Future? This a career-defining opportunity working within More ❯

solutions. Strong engineering fundamentals, including DevOps, CI/CD, and secure ML/AI pipelines (DevSecOps). Highly proficient in Python, SQL, and key AI/ML frameworks (e.g., PyTorch, TensorFlow). Ability to mitigate model hallucination, optimise performance, and lead governance around AI risk and ethical deployment. Ready to Transform the Future? This a career-defining opportunity working within More ❯

field • Proven experience in data science and machine learning, with a focus on natural language processing and LLMs. • Proficiency in programming languages such as Python and libraries like TensorFlow, PyTorch, or similar. • Strong understanding of data preprocessing techniques, feature engineering, and model evaluation metrics. • Experience with secure data handling and the ability to work within restricted environments. • Excellent problem-solving More ❯

deep learning algorithms including the latest multimodal foundation models and generative AI frameworks' exploration, development, and implementation. Extensive experience with common machine learning Python frameworks such as TensorFlow and PyTorch; and Python libraries such as pandas, and computer vision libraries such as OpenCV. Experience in ONNX and TensorRT. Very comfortable working in Linux environment. Familiarity with software development tools and More ❯

multi-objective optimization using machine learning and/or deep learning methods Experienced with common python toolkits for scientific computing (e.g., numpy, pandas, scipy), machine learning (e.g., scikit-learn, pytorch), and cheminformatics/bioinformatics (e.g., rdkit, openeye, biotite, biopython) Familiarity running simulations and training models on high-performance computing (GPU) environments for corporate R&D, innovation labs, or academic research More ❯

What Were Looking For: 02 years of experience in machine learning, applied AI, or data science (personal projects and internships count!) Solid Python skills and familiarity with libraries like PyTorch, TensorFlow, or Hugging Face Transformers Understanding of basic ML concepts and data preprocessing techniques Interest in NLP, unstructured data, and information extraction Eagerness to learn, take feedback, and contribute to More ❯

to sequential data. Experience in domains such as RF, EW, radar, acoustic processing, sensor fusion, autonomy, or space awareness. Proficiency in Python software development. Experience with frameworks like TensorFlow, PyTorch, scikit-learn. Legal right to work in the UK. Publication record in relevant journals or conferences is advantageous. Interest in working in a secure environment is desirable but not essential. More ❯

tools such as HuggingFace, Langchain, and OpenAI Extensive hands-on industry data science experience, leveraging typical machine learning and data science tools including pandas, scikit-learn, and TensorFlow/PyTorch Experience building production-grade machine learning deployments on AWS, Azure, or GCP Experience communicating and/or teaching technical concepts to non-technical and technical audiences alike Passion for collaboration More ❯

tools such as HuggingFace, Langchain, and OpenAI Extensive hands-on industry data science experience, leveraging typical machine learning and data science tools including pandas, scikit-learn, and TensorFlow/PyTorch Experience building production-grade machine learning deployments on AWS, Azure, or GCP Experience communicating and/or teaching technical concepts to non-technical and technical audiences alike Passion for collaboration More ❯

You: Experience: 5+ years of experience in machine learning engineering, preferably in Ad Tech, Mar Tech, or related high-scale environments. Strong proficiency in Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn). Deep understanding of supervised, unsupervised, and reinforcement learning methods. Experience with GCP services such as Vertex AI, BigQuery ML, Dataflow, AI Platform Pipelines, and Dataproc. Solid knowledge More ❯

industry. Expert-level proficiency in Python and extensive experience with data science libraries such as Pandas, NumPy, and Scikit-learn. Deep hands-on experience with deep learning frameworks, particularly PyTorch . Proven experience with statistical analysis , hypothesis testing, and data visualization techniques. Familiarity with computer vision tasks and concepts, with direct experience working with YOLO models being a major plus. More ❯

industry. Expert-level proficiency in Python and extensive experience with data science libraries such as Pandas, NumPy, and Scikit-learn. Deep hands-on experience with deep learning frameworks, particularly PyTorch . Proven experience with statistical analysis , hypothesis testing, and data visualization techniques. Familiarity with computer vision tasks and concepts, with direct experience working with YOLO models being a major plus. More ❯

applying deep learning and generative AI techniques, including implementing custom architectures, pretraining/fine-tuning generative models, building agentic workflows, and deploying solutions with real-world constraints. Familiarity with PyTorch, TensorFlow, JAX or similar frameworks Preferred Qualifications Experience in building AI agents (based on RL, LLMs, etc.) Experience in building multi-agent simulation Background in Large Language Models/NLP More ❯

You: Experience: 5+ years of experience in machine learning engineering, preferably in Ad Tech, Mar Tech, or related high-scale environments. Strong proficiency in Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn). Deep understanding of supervised, unsupervised, and reinforcement learning methods. Experience with GCP services such as Vertex AI, BigQuery ML, Dataflow, AI Platform Pipelines, and Dataproc. Solid knowledge More ❯

You: Experience: 5+ years of experience in machine learning engineering, preferably in Ad Tech, Mar Tech, or related high-scale environments. Strong proficiency in Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn). Deep understanding of supervised, unsupervised, and reinforcement learning methods. Experience with GCP services such as Vertex AI, BigQuery ML, Dataflow, AI Platform Pipelines, and Dataproc. Solid knowledge More ❯

Including you. What you'll need Proven experience in leading data science projects in cybersecurity, fraud, or behavioural analytics. Data Engineering - Deep expertise in Python, ML frameworks (e.g. TensorFlow, PyTorch), and cloud platforms (preferably GCP). Deep Learning Theory & Applications - Strong grasp of anomaly detection, time-series modelling, and deep learning architectures. Experience with LLMs and generative AI in production More ❯

in AI. Candidate Profile Essential skills: Bachelors, Masters, PhD, or equivalent experience in Machine Learning, Computer Science, Maths, Data Science, or related fields. Proficiency in deep learning frameworks like PyTorch or JAX. Strong Python software development skills (knowledge of C++ or other languages is a plus). Familiarity with deep learning fundamentals such as models, optimisation, evaluation, and scaling. Experience More ❯

CD pipelines (GitLab), and containerization (Docker). Strong Python programming skills: Strong programming skills in Python, including its ecosystem for AI/ML, with experience using libraries such as PyTorch, Hugging Face Transformers, scikit-learn, and TensorFlow to build and implement AI-driven solutions. Product mindset: Ability to think from the user's perspective and design solutions that align with More ❯

CD pipelines (GitLab), and containerization (Docker). Strong Python programming skills: Strong programming skills in Python, including its ecosystem for AI/ML, with experience using libraries such as PyTorch, Hugging Face Transformers, scikit-learn, and TensorFlow to build and implement AI-driven solutions. Product mindset: Ability to think from the user's perspective and design solutions that align with More ❯

CD pipelines (GitLab), and containerization (Docker). Strong Python programming skills: Strong programming skills in Python, including its ecosystem for AI/ML, with experience using libraries such as PyTorch, Hugging Face Transformers, scikit-learn, and TensorFlow to build and implement AI-driven solutions. Product mindset: Ability to think from the user's perspective and design solutions that align with More ❯

CD pipelines (GitLab), and containerization (Docker). Strong Python programming skills: Strong programming skills in Python, including its ecosystem for AI/ML, with experience using libraries such as PyTorch, Hugging Face Transformers, scikit-learn, and TensorFlow to build and implement AI-driven solutions. Product mindset: Ability to think from the user's perspective and design solutions that align with 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 ❯