22 of 22 Permanent scikit-learn Jobs in the South East

Essential - Demonstrable experience in Machine Learning, NLP, and GenAI including LLM/SLM fine-tuning and prompt development. Proficiency in Python and data libraries such as Pandas, NumPy, Scikit-learn, PyTorch/TensorFlow. Practical knowledge in SQL/NoSQL databases and API development/integration. Proven ability to analyze model performance and optimize for accuracy, efficiency, and scalability. More ❯

ML, data science, or applied statistics Solid programming skills in Python (or similar languages) Familiarity with data science or AI libraries such as Pandas, NumPy, TensorFlow, PyTorch, or Scikit-learn Strong problem-solving ability and analytical thinking A willingness to learn and work collaboratively in a team environment Nice to Have (But Not Required): Experience from a More ❯

Contribute to improving infrastructure, tooling, and best practices for ML development and deployment. Skills & Experience Essential: Strong programming skills in Python (and frameworks such as PyTorch, TensorFlow, or Scikit-learn). Proven experience in developing and deploying machine learning models in production. Solid understanding of data structures, algorithms, and software engineering principles. Experience with ML pipelines and orchestration More ❯

Contribute to improving infrastructure, tooling, and best practices for ML development and deployment. Skills & Experience Essential: Strong programming skills in Python (and frameworks such as PyTorch, TensorFlow, or Scikit-learn). Proven experience in developing and deploying machine learning models in production. Solid understanding of data structures, algorithms, and software engineering principles. Experience with ML pipelines and orchestration More ❯

Contribute to improving infrastructure, tooling, and best practices for ML development and deployment. Skills & Experience Essential: Strong programming skills in Python (and frameworks such as PyTorch, TensorFlow, or Scikit-learn). Proven experience in developing and deploying machine learning models in production. Solid understanding of data structures, algorithms, and software engineering principles. Experience with ML pipelines and orchestration More ❯

concepts clearly to technical and non-technical stakeholders. Essential Skills & Experience Hands-on experience in ML, NLP, and GenAI (LLM/SLM). Proficiency in Python (Pandas, NumPy, Scikit-learn, PyTorch/TensorFlow). Experience with SQL/NoSQL databases, APIs, and data integration. Exposure to on-premise/open-source AI frameworks. Strong problem-solving and communication More ❯

developments in AI, machine learning, and data science methodologies. Experienced Needed: Masters or PhD in a STEM subject Proficiency in Python, with experience in libraries such as pandas, scikit-learn, TensorFlow, or PyTorch. Solid SQL skills and experience working with relational databases. Exposure to cloud platforms (AWS, GCP, or Azure) would be advantageous. Strong analytical and problem-solving More ❯

Mathematics, Computer Science, Engineering, Physics, or a similar field Strong analytical and problem-solving skills Proficiency in Python or R, and familiarity with data libraries (e.g., Pandas, NumPy, Scikit-learn) Basic understanding of statistics, data modelling, and machine learning techniques Experience working with data (e.g., through coursework, projects, or internships) Good communication skills and ability to explain complex More ❯

package Key Responsibilities: Research and deploy LLM-based solutions (e.g., LangChain, Mastra.ai, Pydantic) for document processing, summarization, and clinical Q&A systems. Develop and optimize predictive models using scikit-learn, PyTorch, TensorFlow, and XGBoost. Design robust data pipelines using tools like Spark and Kafka for real-time and batch processing. Manage ML lifecycle with tools such as Databricks More ❯

discussions and implementing solutions defined by project leads. Desirable Experience Strong Python expertise. Experience with GNU/Linux environments. Familiarity with key data science and ML frameworks (e.g., scikit-learn, PyTorch, TensorFlow, XGBoost, Hugging Face). Experience in natural language processing, tabular data analysis, or computer vision. SQL proficiency. Exposure to containerisation (Docker, Kubernetes) and cloud-native architectures. More ❯

cloud and MLOps tooling to build scalable, reliable solutions Communicating data-driven insights and influencing both technical and business stakeholders What We’re Looking For Expert-level Python (scikit-learn, pandas, etc.), SQL, and big data platforms (e.g. Databricks) Proven experience with MLOps : deploying, monitoring, and scaling models in production Strong cloud experience (AWS, GCP, or Azure) and More ❯

cloud and MLOps tooling to build scalable, reliable solutions Communicating data-driven insights and influencing both technical and business stakeholders What We’re Looking For Expert-level Python (scikit-learn, pandas, etc.), SQL, and big data platforms (e.g. Databricks) Proven experience with MLOps : deploying, monitoring, and scaling models in production Strong cloud experience (AWS, GCP, or Azure) and More ❯

cloud and MLOps tooling to build scalable, reliable solutions Communicating data-driven insights and influencing both technical and business stakeholders What We’re Looking For Expert-level Python (scikit-learn, pandas, etc.), SQL, and big data platforms (e.g. Databricks) Proven experience with MLOps : deploying, monitoring, and scaling models in production Strong cloud experience (AWS, GCP, or Azure) and 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 ❯

insights. What we're looking for: Strong hands-on experience with time-series modelling (ARIMA, VAR, GARCH, Prophet, LSTMs, Transformers, etc.). Proficiency in the Python ecosystem (pandas, scikit-learn, statsmodels, PyTorch/TensorFlow; polars/dask a plus). Familiarity with SQL and handling large datasets. Curiosity and interest in financial markets and macroeconomics . Master's More ❯

a senior data science role. Deep understanding of machine learning model lifecycles and optimisation. Skilled in building, training, and deploying models on large datasets. Proficiency in Python, PyTorch, Scikit-learn, and similar ML frameworks. Experience with cloud environments (AWS preferred), containerisation, and modern data infrastructure. Excellent communication skills, with the ability to work effectively across technical and non More ❯

a senior data science role. Deep understanding of machine learning model lifecycles and optimisation. Skilled in building, training, and deploying models on large datasets. Proficiency in Python, PyTorch, Scikit-learn, and similar ML frameworks. Experience with cloud environments (AWS preferred), containerisation, and modern data infrastructure. Excellent communication skills, with the ability to work effectively across technical and non More ❯

stratigraphy, sedimentology, or petroleum geology. Experience of working with subsurface datasets (e.g., wireline, seismic, biostratigraphy). Strong python programming skills and experience with ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). Excellent communication and teamwork skills in a collaborative R&D environment. AI/ML Implementation: Design and implement AI/ML algorithms to automate and enhance geological More ❯

develop and deliver ML-powered solutions: Model Development : Assist in building and training machine learning and deep learning models using Python and ML frameworks like TensorFlow, PyTorch, or Scikit-learn Data Preparation : Work on collecting, cleaning, transforming, and analysing large datasets for training and testing models Feature Engineering : Support the design and selection of relevant input features to … graduate (or soon-to-be) in Computer Science, Data Science, Engineering, Mathematics, Statistics, Physics, or a related discipline Proficiency in Python and familiarity with ML libraries such as Scikit-learn, TensorFlow, or PyTorch Strong understanding of basic machine learning concepts and algorithms (e.g. regression, classification, decision trees) Good grasp of data structures, algorithms, and programming fundamentals. Analytical mindset More ❯

Machine Learning Engineer £60000 - 90000 GBP Onsite WORKING Location: Central London, Greater London - United Kingdom Type: Permanent Machine Learning Engineer - Defence & National Security Locations: Poole | Hereford | Remote (UK-wide with travel) £60,000 - £90,000 + benefits Our client is More ❯

Senior Machine Learning Engineer £90000 - 100000 GBP Onsite WORKING Location: Central London, Greater London - United Kingdom Type: Permanent Machine Learning Engineer - 6-Month FTC £90,000 - £110,000 UK-wide (Hybrid: London client-site) Our client is a leading AI More ❯

Data Scientist, Machine Learning Engineer, ML Engineer, Data Science Engineer, High-Performance Engineering, Python, Data, Pandas, numpy, scikit-learn, pytorch - Oxford - up to 55K About the Role: Join an elite engineering organisation's Software Engineering & Data team, where you'll develop cutting-edge machine learning solutions that directly impact performance at the highest level of competition. This is … a relevant field for Data Science 2+ years development experience in Python and machine learning techniques (production or laboratory) Strong knowledge of Python data science packages: Pandas, numpy, scikit-learn, pytorch Experience with Machine Learning techniques: Neural Networks, XGBoost Understanding of pipelines and deployment technologies: Azure DevOps, Docker, GitHub Actions Good understanding of architecture and design patterns Excellent More ❯