76 to 100 of 178 Permanent scikit-learn Jobs

We’re Looking For: 🎓 A degree in Artificial Intelligence, Computer Science, Mathematics, or a related field 🐍 Proficiency in Python and experience with frameworks such as PyTorch , NumPy , or Scikit-learn 🧩 Understanding of machine learning algorithms, optimisation, and model evaluation 📈 Strong mathematical reasoning and analytical problem-solving skills 🗣 Excellent communication skills and a genuine passion for learning and innovation More ❯

model management. Strong knowledge of SQL and database management, as well as programming languages such as Python, R, or similar. Strong experience with machine learning frameworks (e.g., TensorFlow, Scikit-learn) as well as familiarity with data technologies (e.g., Hadoop, Spark). About Vixio: Our mission is to empower businesses to efficiently manage and meet their regulatory obligations with More ❯

Strong technical skills, proficient in various programming languages, frameworks, and tools for DLT/Blockchain, data analysis and AI development, such as Solidity (Ethereum), Python, R, TensorFlow, PyTorch, Scikit-learn, etc; Familiar with various data sources, formats, and standards, such as APIs, JSON, XML, CSV, etc, and detail oriented; Experience in developing and deploying applications and solutions using More ❯

analytics and hands-on experience and solid understanding of machine learning and deep learning methods Extensive experience with machine learning and deep learning toolkits (e.g.: TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas) Ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals Preferred Qualifications, Capabilities, and More ❯

in artificial intelligence and its application to drug discovery Understanding of ligand- and structure-based drug design. Experience with machine learning and major machine learning frameworks such as scikit-learn or PyTorch Proficiency in a low-level programming language such as C/C++ or Rust. Knowledge of advanced data analysis techniques such as multi-parameter optimization Open More ❯

experience. Proven experience designing and deploying MLOps pipelines (MLflow, Azure ML, Azure DevOps etc). Strong programming skills in Python and familiarity with common ML/AI libraries (scikit-learn, tensorflow, Keras etc.). Experience implementing machine learning and large language models (LLMs), encompassing deployment, monitoring, and retraining. Familiarity with software engineering guidelines: version control (e.g., Git), CI More ❯

experience with Python. Rust and C++ are nice to have. 3+ years designing and building data-intensive solutions with distributed computing. 2+ years with industry-recognized ML frameworks (scikit-learn, PyTorch, TensorFlow, Spark, Ray). 1+ year productionizing, monitoring, and maintaining models. Bachelor's degree or equivalent work experience. Preferred Qualifications: 1+ years building, scaling, and optimizing ML More ❯

sensor time-series) data and decision-making post PhD Experience in software development for proof of concept in Python Experience with machine and deep learning frameworks: TensorFlow, PyTorch, scikit-learn, etc. Of particular interest are candidates with experience in one or more of the following domains: RF communications and CEMA Electronic or Electromagnetic Warfare (EW) Tracking and sensor More ❯

and SQL Experience with API platforms such as Postman, Azure API Management or Boomi Experience with BI frameworks and MS Excel Proficiency in Microsoft Office tools Experience in SciKit Learn, TensorFlow, Pytorch, XGBoost,or equivalent libraries. Preferred Qualifications: Experience with Openings Studio in practical or field application, otherwise functional experience in the construction or manufacturing industry Functional knowledge More ❯

machine learning lifecycle Working with Data Scientists to deploy trained machine learning models into production environments Working with a range of models developed using common frameworks such as Scikit-learn, TensorFlow, or PyTorch Experience with software engineering best practices and developing applications in Python. Technical experience of cloud architecture, security, deployment, and open-source tools ideally with one More ❯

machine learning lifecycle Working with Data Scientists to deploy trained machine learning models into production environments Working with a range of models developed using common frameworks such as Scikit-learn, TensorFlow, or PyTorch Experience with software engineering best practices and developing applications in Python. Technical experience of cloud architecture, security, deployment, and open-source tools ideally with one More ❯

machine learning lifecycle Working with Data Scientists to deploy trained machine learning models into production environments Working with a range of models developed using common frameworks such as Scikit-learn, TensorFlow, or PyTorch Experience with software engineering best practices and developing applications in Python. Technical experience of cloud architecture, security, deployment, and open-source tools ideally with one More ❯

machine learning lifecycle Working with Data Scientists to deploy trained machine learning models into production environments Working with a range of models developed using common frameworks such as Scikit-learn, TensorFlow, or PyTorch Experience with software engineering best practices and developing applications in Python. Technical experience of cloud architecture, security, deployment, and open-source tools ideally with one More ❯

background will include: 3+ years industry experience in a Data Science role and a strong academic background Python Data Science Stack: Advanced proficiency in Python , including pandas , NumPy , scikit-learn , and Jupyter Notebooks . Statistical & ML Modelling: Strong foundation in statistical analysis and proven experience applying a range of machine learning techniques to solve business problems (e.g., regression More ❯

the end-to-end machine learning lifecycle, including data ingestion, preprocessing, model training, deployment, and production monitoring 3+ years of experience with modern machine learning tools and libraries (scikit-learn, PyTorch, TensorFlow, spaCy, etc) with strong proficiency in Python 3+ years of experience with any of the following fundamental AI technologies: vector search, embedding models, recommender systems, supervised More ❯

limitations. What you’ve done 3+ years in Data Science/Analytics (or 2+ with a strong portfolio) delivering models into production. Strong Python (pandas/numpy/scikit-learn; XGBoost/LightGBM; basic PyTorch a plus) and SQL. Solid geospatial skills (PostGIS/GeoPandas/QGIS) and time-series/forecasting know-how. ETL/ELT and More ❯

technical audiences Right to work in the UK Strong academic background (GCSEs, A-Levels or equivalent) Desirable (but not essential) Experience with Python libraries like Pandas, NumPy, or Scikit-learn Exposure to machine learning concepts or blockchain architecture Coursework or personal projects involving data analysis, AI/ML, or distributed systems Knowledge of data visualisation tools like Power More ❯

a quantitative field (e.g. Statistics, Mathematics, Physics, Machine Learning) You're confident in Python (production-level) and SQL, and at home with modern ML libraries such as Pandas, scikit-learn, and TensorFlow You have practical experience with MLOps frameworks and deploying models You're skilled at bringing data to life through visualisation, and tools like Tableau feel natural More ❯

research PhD, or a Master's degree and experience building machine learning models or developing algorithms for business application Preferred Qualifications 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. Amazon is an equal opportunities employer. We believe passionately that More ❯

of key machine learning models, including Gradient Boosting Machines (GBMs), Neural Networks and Large language models (LLMs). Hands-on experience with popular machine learning libraries such as Scikit-learn, XGBoost, LightGBM, TensorFlow, or PyTorch. Knowledge of AWS products and services including Sagemaker. Deep knowledge of Microsoft Excel in a commercial setting. You enjoy being Agile - you should More ❯

and code generation toolsets for API development. Some experience with Python, modern development techniques, and design patterns. Experience in data science tools and ML tools (e.g., NumPy, pandas, scikit-learn, PyTorch) and open-source contributions (especially Python-based) would be a bonus. Familiarity with CUDA, GPU-based computations, end-to-end neural network training, MLOps, and academic research More ❯

and code generation toolsets for API development. Some experience with Python, modern development techniques, and design patterns. Experience in data science tools and ML tools (e.g., NumPy, pandas, scikit-learn, PyTorch) and open-source contributions (especially Python-based) would be a bonus. Familiarity with CUDA, GPU-based computations, end-to-end neural network training, MLOps, and academic research More ❯

and code generation toolsets for API development. Some experience with Python, modern development techniques, and design patterns. Experience in data science tools and ML tools (e.g., NumPy, pandas, scikit-learn, PyTorch) and open-source contributions (especially Python-based) would be a bonus. Familiarity with CUDA, GPU-based computations, end-to-end neural network training, MLOps, and academic research More ❯

and code generation toolsets for API development. Some experience with Python, modern development techniques, and design patterns. Experience in data science tools and ML tools (e.g., NumPy, pandas, scikit-learn, PyTorch) and open-source contributions (especially Python-based) would be a bonus. Familiarity with CUDA, GPU-based computations, end-to-end neural network training, MLOps, and academic research More ❯

and code generation toolsets for API development. Some experience with Python, modern development techniques, and design patterns. Experience in data science tools and ML tools (e.g., NumPy, pandas, scikit-learn, PyTorch) and open-source contributions (especially Python-based) would be a bonus. Familiarity with CUDA, GPU-based computations, end-to-end neural network training, MLOps, and academic research More ❯