26 to 50 of 143 scikit-learn Jobs in London

with supervised and unsupervised learning, NLP, neural networks, Bayesian statistics, time-series forecasting, collaborative filtering, and deep learning Proficiency in Python and ML libraries (e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) Experience with cloud platforms (GCP, AWS, Azure) and tools like Dataiku and Databricks Experience with ML Ops, including deployment, monitoring, and retraining pipelines Ability to work More ❯

with supervised and unsupervised learning, NLP, neural networks, Bayesian statistics, time-series forecasting, collaborative filtering, and deep learning Proficiency in Python and ML libraries (e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) Experience with cloud platforms (GCP, AWS, Azure) and tools like Dataiku and Databricks Experience with ML Ops, including deployment, monitoring, and retraining pipelines Ability to work More ❯

with a track record of taking ML projects from conception to deployment in a cloud environment (AWS preferred). Strong proficiency in Python for data science (Pandas, NumPy, Scikit-learn) and SQL (PostgreSQL is a plus). Hands-on experience with the full data lifecycle: data ingestion (e.g., web-scraping with BeautifulSoup, Scrapy, or Selenium), data wrangling, model More ❯

recommendation systems and deep learning architectures Strong understanding of two-tower neural networks, embedding techniques, and ranking models Proficiency in Python and ML libraries (e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku Experience with ML Ops, including deployment, monitoring, and retraining pipelines Ability to work cross-functionally More ❯

recommendation systems and deep learning architectures Strong understanding of two-tower neural networks, embedding techniques, and ranking models Proficiency in Python and ML libraries (e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku Experience with ML Ops, including deployment, monitoring, and retraining pipelines Ability to work cross-functionally More ❯

recommendation systems and deep learning architectures Strong understanding of two-tower neural networks, embedding techniques, and ranking models Proficiency in Python and ML libraries (e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku Experience with ML Ops, including deployment, monitoring, and retraining pipelines Ability to work cross-functionally More ❯

Collaborate with data scientists, software engineers, and subject-matter experts to deliver innovative solutions. Essential Skills & Experience Advanced Python programming skills with hands-on experience using NumPy, Pandas, Scikit-learn, Langchain, LlamaIndex , and Azure AI Foundry . Proven experience working with Azure cloud services and Generative AI R&D. Strong understanding of machine learning, data modelling , and natural More ❯

Data Scientist , ideally in a government or large-scale enterprise environment. Strong Python programming skills, including experience with data science and AI/ML frameworks (e.g., Pandas, NumPy, Scikit-learn, PyTorch, TensorFlow). Experience developing and fine-tuning LLMs and working with generative AI tools. Hands-on experience with Microsoft Azure (Azure ML, Databricks, or other AI services More ❯

Data Scientist , ideally in a government or large-scale enterprise environment. Strong Python programming skills, including experience with data science and AI/ML frameworks (e.g., Pandas, NumPy, Scikit-learn, PyTorch, TensorFlow). Experience developing and fine-tuning LLMs and working with generative AI tools. Hands-on experience with Microsoft Azure (Azure ML, Databricks, or other AI services More ❯

tooling (e.g., MLflow, Kubeflow, Vertex AI, SageMaker, Azure ML). • Hands-on experience with data science tools and languages such as Python, R, SQL, and relevant frameworks (e.g., scikit-learn, TensorFlow, PyTorch). • Proven ability to assess or design organizational processes for data science delivery and model management. • Excellent analytical and communication skills, with the ability to synthesize More ❯

tooling (e.g., MLflow, Kubeflow, Vertex AI, SageMaker, Azure ML). • Hands-on experience with data science tools and languages such as Python, R, SQL, and relevant frameworks (e.g., scikit-learn, TensorFlow, PyTorch). • Proven ability to assess or design organizational processes for data science delivery and model management. • Excellent analytical and communication skills, with the ability to synthesize More ❯

tooling (e.g., MLflow, Kubeflow, Vertex AI, SageMaker, Azure ML). • Hands-on experience with data science tools and languages such as Python, R, SQL, and relevant frameworks (e.g., scikit-learn, TensorFlow, PyTorch). • Proven ability to assess or design organizational processes for data science delivery and model management. • Excellent analytical and communication skills, with the ability to synthesize More ❯

tooling (e.g., MLflow, Kubeflow, Vertex AI, SageMaker, Azure ML). • Hands-on experience with data science tools and languages such as Python, R, SQL, and relevant frameworks (e.g., scikit-learn, TensorFlow, PyTorch). • Proven ability to assess or design organizational processes for data science delivery and model management. • Excellent analytical and communication skills, with the ability to synthesize More ❯

and deep learning architectures. Strong understanding of two-tower neural networks, embedding techniques, and ranking models. Proficiency in Python with familiarity to ML libraries e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku. Experience with ML Ops, including model deployment, monitoring, and retraining pipelines. Ability to work cross More ❯

depth knowledge of how they work Python: You have built and deployed production-grade Python applications and you are familiar with data science libraries such as pandas and scikit-learn Tooling & Environment : DevOps: You have experience working with DevOps tooling, such as gitops, Kubernetes, CI/CD tools (we use buildkite) and Docker Cloud: You have worked with More ❯

and deep learning architectures. Strong understanding of two-tower neural networks, embedding techniques, and ranking models. Proficiency in Python with familiarity to ML libraries e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku. Experience with ML Ops, including model deployment, monitoring, and retraining pipelines. Ability to work cross More ❯

and deep learning architectures. Strong understanding of two-tower neural networks, embedding techniques, and ranking models. Proficiency in Python with familiarity to ML libraries e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku. Experience with ML Ops, including model deployment, monitoring, and retraining pipelines. Ability to work cross More ❯

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 ❯

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 ❯

Exposure to courses related to Artificial Intelligence, Machine Learning, or Natural Language Processing Familiarity with frameworks like Express.js, Flask, or NestJS Familiarity with libraries like TensorFlow, PyTorch, or scikit-learn Basic understanding of Amazon Web Services Culture: Coffee and snacks in the office Team socials Inclusive working environment, supporting all genders, sexualities, race, disability or background Join our More ❯

model accuracy and interpretability. Develop and validate machine learning and statistical models for prediction, classification, clustering, or optimization. Apply supervised and unsupervised learning techniques using libraries such as Scikit-learn, TensorFlow, or PyTorch. Implement NLP, time-series forecasting, or optimization algorithms based on project requirements. Evaluate models using appropriate metrics and perform hyperparameter tuning for optimal performance. Convert More ❯

ML/NLP community Technical Skills: Degree in Computer Science, Engineering, Bioinformatics, or related field (BSc, MSc, PhD) Experience with ML/NLP frameworks (e.g., PyTorch, TensorFlow, HuggingFace, Scikit-learn) Strong Python skills and familiarity with additional languages (e.g., Java, C++) Understanding of biomedical ontologies, knowledge graphs, or causal inference is a plus Familiarity with cloud platforms (AWS More ❯

ML/NLP community Technical Skills: Degree in Computer Science, Engineering, Bioinformatics, or related field (BSc, MSc, PhD) Experience with ML/NLP frameworks (e.g., PyTorch, TensorFlow, HuggingFace, Scikit-learn) Strong Python skills and familiarity with additional languages (e.g., Java, C++) Understanding of biomedical ontologies, knowledge graphs, or causal inference is a plus Familiarity with cloud platforms (AWS More ❯

For Strong software engineering skills, especially in Python. Experience building robust systems for ML applications Proven track record deploying machine learning models in production (using frameworks such as Scikit-learn, TensorFlow, or PyTorch) Practical experience working with cloud infrastructure (e.g., AWS, Azure, GCP) and a good understanding of architecture, security, and scaling Hands-on experience with Docker and More ❯