126 to 150 of 224 scikit-learn Jobs in London

experience working within areas such as NLP, LLM, recommendation systems Information Retrieval stacks, GenAI (specifically RAG systems). Familiar with architecture and implementation of 1+ ML frameworks (PyTorch, scikit-learn). Experience working in the full model lifecycle (including experimentation, training, testing, monitoring, and deployment). Good knowledge of AWS’s machine learning infrastructure. Again this is a More ❯

experience working within areas such as NLP, LLM, recommendation systems Information Retrieval stacks, GenAI (specifically RAG systems). Familiar with architecture and implementation of 1+ ML frameworks (PyTorch, scikit-learn). Experience working in the full model lifecycle (including experimentation, training, testing, monitoring, and deployment). Good knowledge of AWS’s machine learning infrastructure. Again this is a More ❯

What We're Looking For A Bachelor's degree in Computer Science, Mathematics, Electrical Engineering, or a related field. Strong experience with Python and data science libraries (Pandas, Scikit-learn, etc.). Solid understanding of machine learning concepts and algorithms . Interest in working with real-world industrial or sensor data . Exposure to Apache Airflow and/ More ❯

to deadline. Experience in Deep Learning and DL frameworks such as Tensorflow/Pytroch Deploying ML models Good command of Python and use of libraries for data science – scikit-learn, NumPy, matplotlib Relation database experience with data manipulation skills in SQL and large “Big Data” environments. Command knowledge in Python and API Development Excellent grasp of software Engineering More ❯

to deadline. Experience in Deep Learning and DL frameworks such as Tensorflow/Pytroch Deploying ML models Good command of Python and use of libraries for data science – scikit-learn, NumPy, matplotlib Relation database experience with data manipulation skills in SQL and large “Big Data” environments. Command knowledge in Python and API Development Excellent grasp of software Engineering More ❯

enterprise-scale AI applications, and mentoring a team of talented data scientists. Deep expertise in machine learning and statistical modelling Skilled with core data science tools (NumPy, Pandas, Scikit-Learn) and deep learning frameworks (PyTorch, TensorFlow) &##Proven track record delivering impactful AI/ML projects (e.g. forecasting, recommendation systems, or optimisation) &##Experienced project lead with strong technical decision More ❯

to deadline. Experience in Deep Learning and DL frameworks such as Tensorflow/Pytroch Deploying ML models Good command of Python and use of libraries for data science – scikit-learn, NumPy, matplotlib Relation database experience with data manipulation skills in SQL and large “Big Data” environments. Command knowledge in Python and API Development Excellent grasp of software Engineering More ❯

to deadline. Experience in Deep Learning and DL frameworks such as Tensorflow/Pytroch Deploying ML models Good command of Python and use of libraries for data science – scikit-learn, NumPy, matplotlib Relation database experience with data manipulation skills in SQL and large “Big Data” environments. Command knowledge in Python and API Development Excellent grasp of software Engineering More ❯

reproducibility 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) AWS, Azure, GCP) and a good understanding of architecture, security, and scaling Solid grasp of ML fundamentals: supervised/unsupervised learning, statistical modelling, evaluation A More ❯

and mentoring a team of talented data scientists. What You’ll Bring 🔥 Deep expertise in machine learning and statistical modelling ⚙️ Skilled with core data science tools (NumPy, Pandas, Scikit-Learn) and deep learning frameworks (PyTorch, TensorFlow) 💡 Proven track record delivering impactful AI/ML projects (e.g. forecasting, recommendation systems, or optimisation) 📈 Experienced project lead with strong technical decision More ❯

and mentoring a team of talented data scientists. What You’ll Bring 🔥 Deep expertise in machine learning and statistical modelling ⚙️ Skilled with core data science tools (NumPy, Pandas, Scikit-Learn) and deep learning frameworks (PyTorch, TensorFlow) 💡 Proven track record delivering impactful AI/ML projects (e.g. forecasting, recommendation systems, or optimisation) 📈 Experienced project lead with strong technical decision More ❯

and mentoring a team of talented data scientists. What You’ll Bring 🔥 Deep expertise in machine learning and statistical modelling ⚙️ Skilled with core data science tools (NumPy, Pandas, Scikit-Learn) and deep learning frameworks (PyTorch, TensorFlow) 💡 Proven track record delivering impactful AI/ML projects (e.g. forecasting, recommendation systems, or optimisation) 📈 Experienced project lead with strong technical decision More ❯

and mentoring a team of talented data scientists. What You’ll Bring 🔥 Deep expertise in machine learning and statistical modelling ⚙️ Skilled with core data science tools (NumPy, Pandas, Scikit-Learn) and deep learning frameworks (PyTorch, TensorFlow) 💡 Proven track record delivering impactful AI/ML projects (e.g. forecasting, recommendation systems, or optimisation) 📈 Experienced project lead with strong technical decision More ❯

strong problem-solving skills, a quick learning ability, and enthusiasm for tackling complex challenges. You are proficient in Python, with experience using PySpark and ML libraries such as scikit-learn, TensorFlow, or Keras . You are familiar with big data technologies (e.g., Hadoop, Spark), cloud platforms (AWS, GCP), and can effectively communicate technical concepts to non-technical stakeholders. More ❯

ICCV, or ECCV). Deep experience with modern vision architectures such as YOLO , Vision Transformers , and EVA . Strong command of Python and core ML libraries (NumPy, pandas, scikit-learn, TensorFlow, PyTorch). Familiarity with MLOps practices and evaluation metrics (Accuracy, Recall, F1, IoU, etc.). Excellent communication and problem-solving skills; ability to engage with both technical More ❯

ICCV, or ECCV). Deep experience with modern vision architectures such as YOLO , Vision Transformers , and EVA . Strong command of Python and core ML libraries (NumPy, pandas, scikit-learn, TensorFlow, PyTorch). Familiarity with MLOps practices and evaluation metrics (Accuracy, Recall, F1, IoU, etc.). Excellent communication and problem-solving skills; ability to engage with both technical More ❯

ICCV, or ECCV). Deep experience with modern vision architectures such as YOLO , Vision Transformers , and EVA . Strong command of Python and core ML libraries (NumPy, pandas, scikit-learn, TensorFlow, PyTorch). Familiarity with MLOps practices and evaluation metrics (Accuracy, Recall, F1, IoU, etc.). Excellent communication and problem-solving skills; ability to engage with both technical More ❯

ICCV, or ECCV). Deep experience with modern vision architectures such as YOLO , Vision Transformers , and EVA . Strong command of Python and core ML libraries (NumPy, pandas, scikit-learn, TensorFlow, PyTorch). Familiarity with MLOps practices and evaluation metrics (Accuracy, Recall, F1, IoU, etc.). Excellent communication and problem-solving skills; ability to engage with both technical More ❯

NumPy, Pandas, SciPy) • SQL or time-series DBs • Linux & distributed systems expertise • Strong communication & market intuition ✨ Bonus Skills • KDB+/Q, Haskell, or other functional languages • Machine learning (scikit-learn, etc.) • Quant tools & mathematical background • Docker, Kubernetes, AWS 📍 Location : London (1 remote day per week) 💼 Type : Full-time | Competitive comp + performance bonus Ready to build systems that More ❯

NumPy, Pandas, SciPy) • SQL or time-series DBs • Linux & distributed systems expertise • Strong communication & market intuition ✨ Bonus Skills • KDB+/Q, Haskell, or other functional languages • Machine learning (scikit-learn, etc.) • Quant tools & mathematical background • Docker, Kubernetes, AWS 📍 Location : London (1 remote day per week) 💼 Type : Full-time | Competitive comp + performance bonus Ready to build systems that More ❯

NumPy, Pandas, SciPy) • SQL or time-series DBs • Linux & distributed systems expertise • Strong communication & market intuition ✨ Bonus Skills • KDB+/Q, Haskell, or other functional languages • Machine learning (scikit-learn, etc.) • Quant tools & mathematical background • Docker, Kubernetes, AWS 📍 Location : London (1 remote day per week) 💼 Type : Full-time | Competitive comp + performance bonus Ready to build systems that More ❯

NumPy, Pandas, SciPy) • SQL or time-series DBs • Linux & distributed systems expertise • Strong communication & market intuition ✨ Bonus Skills • KDB+/Q, Haskell, or other functional languages • Machine learning (scikit-learn, etc.) • Quant tools & mathematical background • Docker, Kubernetes, AWS 📍 Location : London (1 remote day per week) 💼 Type : Full-time | Competitive comp + performance bonus Ready to build systems that More ❯

Azure AI Services). Experience with a major conversational AI platform (Google Dialogflow, Amazon Lex, Rasa, or similar). A solid understanding of core Python ML libraries (Keras, scikit-learn, Pandas) and deep learning frameworks (TensorFlow, PyTorch). Desirable (but not essential) experience: Working with tools/interfaces for AI applications e.g. MCP protocol. Training traditional ML and More ❯

Azure AI Services). Experience with a major conversational AI platform (Google Dialogflow, Amazon Lex, Rasa, or similar). A solid understanding of core Python ML libraries (Keras, scikit-learn, Pandas) and deep learning frameworks (TensorFlow, PyTorch). Desirable (but not essential) experience: Working with tools/interfaces for AI applications e.g. MCP protocol. Training traditional ML and More ❯

experience, with 4+ years focused on ML systems Must have expertise in Knowledge Graphs and Graph Databases (Neo4j preferred) Advanced proficiency in Python, including ML libraries (e.g., PyTorch, scikit-learn) Strong experience with distributed systems, data engineering, and API development Proficiency in both SQL and NoSQL databases Familiarity with Docker, Kubernetes, and CI/CD pipelines Experience integrating More ❯