7 of 7 Remote/Hybrid scikit-learn Jobs in the UK excluding London

cost efficiency, performance and scalability against standard benchmarks.18. Stay ahead of developments in GenAI (e.g. LLMs, multimodal models), ML frameworks (e.g. PyTorch, TensorFlow, Scikit-learn), orchestration tools (e.g. LangChain, LangFuse), model hubs. Taking responsibility for your own continuous professional development.19. Fostering a culture of responsible innovation and continuous ...

expertise with hands-on experience productionising models and building scalable ML systems. Machine Learning Engineer, key skills: Strong experience in Python (e.g. pandas, scikit-learn, NumPy, TensorFlow/PyTorch) Proven experience in model productionisation and deployment in real-world environments Hands-on experience with MLOps, including CI/ ...

mentor engineers and scientists, lead applied research initiatives What You'll Bring Technical Expertise: Strong Python skills with the ML stack: NumPy, pandas, scikit-learn Hands-on experience with at least one deep learning framework (PyTorch, TensorFlow, JAX) Solid grounding in core ML—supervised, unsupervised, evaluation, regularisation, statistics ...

Solid understanding of Scrum practices and a strong Agile mindset. Advanced proficiency in Python and its key data and ML libraries (NumPy, PySpark, Scikit learn, TensorFlow/PyTorch) Working knowledge of generative AI models (e.g., ChatGPT, Claude), Databricks GenAI tooling (including embedding models), and modern data structures such ...

model prototyping to production deployment, integration, and ongoing monitoring. You are proficient in Python and its data/ML ecosystem (e.g. pandas, scikit-learn, PyTorch, TensorFlow), and you can apply statistical and machine learning techniques confidently in real-world settings. You have deployed models into live systems ...

product teams to transform raw data into robust, auditable, and commercially valuable solutions. Skills & Experience Technical Expertise Strong proficiency in Python (Pandas, NumPy, Scikit-learn) and SQL . Hands-on experience with Snowflake or similar cloud-based data warehouse platforms. Experience using Git and reproducible development practices. Strong ...

data and implementing data science processes. Experience in translating customer requirements intotechnical requirements and development objectives. Pythonexpertisecovering standard data sciencelibraries (NumPy, pandas, matplotlib, Scikit-learn,PyTorch, etc),web frameworks (Flask or FastAPI) and visualisation(Dash,Plotly,&Streamlit). Proficient inSQL. Working with unstructured data Building customer and stakeholder ...