1 to 25 of 33 scikit-learn Jobs in the South West

professional experience in machine learning engineering. 2+ years of leadership or technical mentoring experience. Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning More ❯

professional experience in machine learning engineering. 2+ years of leadership or technical mentoring experience. Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning More ❯

professional experience in machine learning engineering. 2+ years of leadership or technical mentoring experience. Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning More ❯

professional experience in machine learning engineering. 2+ years of leadership or technical mentoring experience. Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning More ❯

professional experience in machine learning engineering. 2+ years of leadership or technical mentoring experience. Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning More ❯

professional experience in machine learning engineering. 2+ years of leadership or technical mentoring experience. Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning More ❯

professional experience in machine learning engineering. 2+ years of leadership or technical mentoring experience. Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning More ❯

professional experience in machine learning engineering. 2+ years of leadership or technical mentoring experience. Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning More ❯

Active EDV/UK*C security clearance. Proficient in Python and/or R, with experience using data science libraries (e.g., Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch). Strong statistical, mathematical, and data modelling skills. Experience with data visualisation tools (e.g., Power BI, Tableau, matplotlib, Plotly). Familiarity More ❯

be able to hold or gain a UK government security clearance. Preferred Technical And Professional Experience Experience with machine learning frameworks (TensorFlow, PyTorch, scikit-learn). Familiarity with big data technologies (Hadoop, Spark). Background in data science, IT consulting, or a related field. AWS Certified Big Data More ❯

techniques for solving problems, ideally including Large Language Models. Proficiency in Python, particularly with machine learning and data science libraries such as PyTorch, scikit-learn, numpy and scipy. Good communication and interpersonal skills. Experience working with large-scale data processing systems such as Spark and Hadoop. Experience in More ❯

techniques for solving problems, ideally including Large Language Models Proficiency in Python, particularly with machine learning and data science libraries such as PyTorch, scikit-learn, numpy and scipy Good communication and interpersonal skills Experience working with large-scale data processing systems such as Spark and Hadoop Experience in More ❯

We’re Looking For: 2+ years of experience building and deploying machine learning models Strong programming skills in Python and ML frameworks (e.g., scikit-learn, TensorFlow, PyTorch) Experience with model evaluation, tuning, and productionisation Exposure to cloud platforms (e.g., Azure, AWS, or GCP) and containerisation tools (e.g., Docker More ❯

science methods using both quantitative and qualitative metrics. Strong mathematical and statistical background. Deep knowledge of Python and data science packages such as Scikit learn, Keras, Tensor flow, and PySpark. Experience and understanding of mixed technical teams such as engineering, architects, business analysts. Familiar with MLOps industry best More ❯

science methods using both quantitative and qualitative metrics. Strong mathematical and statistical background. Deep knowledge of Python and data science packages such as Scikit learn, Keras, Tensor flow, and PySpark. Experience and understanding of mixed technical teams such as engineering, architects, business analysts. Familiar with MLOps industry best More ❯

record of leading complex AI projects in an agile environment Strong technical proficiency with modern ML tools and frameworks: PyTorch, TensorFlow, SparkMLLib, SciPy, Scikit-Learn, NLTK (etc) MLflow or similar ML lifecycle tools Cloud platforms (AWS/Azure/GCP) Experience with AI governance and responsible AI practices More ❯

proficiency in Python and one additional language (e.g. C++, Java, Scala) Experience with ML frameworks (e.g. PyTorch, TensorFlow), and scientific libraries (NumPy, SciPy, scikit-learn) Familiarity with audio data (or video), able to handle large binary files Proven experience in at least one of: ML model deployment, ML More ❯

etc.) Understanding of transfer learning and popular augmentation techniques Able to apply machine learning to real-life problems Vision Transformers, DeepLabv3, SegFormer, etc.Python, Scikit-Learn, NumPy, Pandas and PyTorch/TensorFlow/Keras Thrive in a cross-functional working environment Possess a clear passion for data science beyond More ❯

in AI/ML implementation, ideally within marketing, media, or eCommerce. Proficiency in Python and relevant AI/ML libraries (e.g., TensorFlow, PyTorch, scikit-learn). Experience with cloud platforms (AWS, GCP, or Azure) and deploying AI models in production. A strategic mindset with the ability to balance More ❯

development, testing, and operational stability. Proficient in coding in Python. Proficient in the use of basic data science libraries in Python (NumPy, pandas, scikit-learn, pyspark). Experience in developing, debugging, and maintaining code in a large corporate environment with modern programming languages and database querying languages. Overall More ❯

ability to understand and translate data into actionable insights for the business. Strong working knowledge of Python and data science packages such as Scikit learn, Keras, Tensor flow and PySpark. Good understanding of industry standard MLOps capabilities. Understanding of the financial industry, in particular insurance, would be advantageous. More ❯

ability to understand and translate data into actionable insights for the business. Strong working knowledge of Python and data science packages such as Scikit learn, Keras, Tensor flow and PySpark. Good understanding of industry standard MLOps capabilities. Understanding of the financial industry, in particular insurance, would be advantageous. More ❯

Key Skills Required: Comprehensive understanding of the full machine learning lifecycle, from development to production. Experience deploying machine learning models using frameworks like Scikit-learn, TensorFlow, or PyTorch. Proficiency in Python and adherence to software engineering best practices. Strong technical expertise in cloud architecture, security, and deployment, with More ❯

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 More ❯

you will have the opportunity to develop skills with the following tools and platforms: Matlab and Simulink Python Deep Learning libraries (e.g. Pytorch, scikit-learn, ONNX) C/C++ Hardware development boards (e.g. NVIDIA Jetson products) Alongside involvement with departmental activities, you will be part of a wider More ❯