101 to 125 of 246 Permanent scikit-learn Jobs

AI services, model deployment, monitoring, and CI/CD pipelines for ML models (MLOps best practices). Example Tools & Technologies: Frameworks & Libraries: LangChain, Hugging Face Transformers, PyTorch, TensorFlow, Scikit-learn Agentic AI Tools: OpenAI GPT models, Crew,AI, Cohere, Pinecone (for vector databases), AutoGPT Data Engineering & ML Pipelines: Apache Airflow, MLflow, Kubeflow, dbt, Prefect Cloud & Deployment Platforms: AWS More ❯

from pipelining to model deployment , Experience with some of the following tools and technologies (or an eagerness to learn): , Python and its data science ecosystem (e.g., pandas, scikit-learn, TensorFlow/PyTorch) , Statistical methods and machine learning (e.g., A/B testing, model validation) , Data pipelining tools like SQL, dbt, BigQuery, or Spark , A strong communicator with More ❯

us again, and again. Proven track record delivering impactful ML/AI solutions in production. Deep expertise in Python and modern AI/ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn, NumPy, Pandas). Hands-on experience with GenAI, agentic AI, and automated testing for AI systems. Curiosity and creativity to challenge assumptions and explore new approaches. Strong communication More ❯

example: supervised/unsupervised machine learning, model cross-validation, Bayesian inference, and time-series analysis An excellent proficiency of the basic libraries for data science (e.g. NumPy, Pandas, Scikit-Learn) and familiarity with a deep-learning framework (e.g. TensorFlow, PyTorch) Demonstrable experience enabling impactful change with AI within a financial services institution. Coupling that with prior experience in More ❯

prem equivalents (e.g., logging, tracing, metrics). Knowledge of data processing frameworks (e.g., Pandas, Spark, Airflow) is a plus. Comfortable reading and working with Python-based ML code (scikit-learn, TensorFlow, PyTorch, etc.). Strong ownership mindset and a collaborative attitude. Nice to Have Experience with model versioning and ML serving frameworks (e.g., MLflow, Seldon, Triton). Understanding More ❯

PhD (or equivalent experience) in a relevant discipline Deep knowledge of machine learning and statistical signal processing Strong Python skills and familiarity with frameworks like PyTorch, TensorFlow, and scikit-learn Experience working with time-series, sensor, or RF data Track record of delivering innovative solutions in complex technical domains Please note: Due to the nature of the work More ❯

Python) CI/CD pipelines, unit testing, use of version control systems. Dashboarding and Data Visualization Skills (e.g. Streamlit, Dash, Retool, Plotly) Exposure to ML libraries/systems (Scikit-learn, PyTorch, MLflow) Clinical trials Good Clinical Practice (GCP) Medical device development About Us All our benefits information can be found in the downloadable Benefits document under 'Information' on More ❯

data science or a quantitative academic field. Strong programming skills, with the ability to quickly become fluent in Python. Deep knowledge of core data science libraries (NumPy, Pandas, Scikit-Learn) and at least one deep learning framework (TensorFlow, PyTorch, or similar). High mathematical and statistical competence, with the ability to design new algorithms when needed. Experience leading More ❯

and multi-objective optimization using machine learning and/or deep learning methods Experienced with common python toolkits for scientific computing (e.g., numpy, pandas, scipy), machine learning (e.g., scikit-learn, pytorch), and cheminformatics/bioinformatics (e.g., rdkit, openeye, biotite, biopython) Familiarity running simulations and training models on high-performance computing (GPU) environments for corporate R&D, innovation labs More ❯

from pipelining to model deployment. Experience with some of the following tools and technologies (or an eagerness to learn): Python and its data science ecosystem (e.g., pandas, scikit-learn, TensorFlow/PyTorch). Statistical methods and machine learning (e.g., A/B testing, model validation). Data pipelining tools like SQL, dbt, BigQuery, or Spark. A strong More ❯

Docker). Strong Python programming skills: Strong programming skills in Python, including its ecosystem for AI/ML, with experience using libraries such as PyTorch, Hugging Face Transformers, scikit-learn, and TensorFlow to build and implement AI-driven solutions. Product mindset: Ability to think from the user's perspective and design solutions that align with developer needs, improving More ❯

Docker). Strong Python programming skills: Strong programming skills in Python, including its ecosystem for AI/ML, with experience using libraries such as PyTorch, Hugging Face Transformers, scikit-learn, and TensorFlow to build and implement AI-driven solutions. Product mindset: Ability to think from the user's perspective and design solutions that align with developer needs, improving More ❯

or e-commerce - this is essential as you'll be the domain expert from day one. Excellent Python programming skills and strong familiarity with ML libraries such as scikit-learn, XGBoost, TensorFlow, PyTorch, Keras etc. Proven track record deploying ML models to production (API, batch, or streaming contexts) Solid understanding of the modern software engineering, infrastructure and data More ❯

BRING: 5+ years of software development experience in quantitative trading, with deep expertise in Java and/or Python. Proficient in Python's data science ecosystem (Pandas, NumPy, Scikit-learn), with strong debugging and analytical skills. Proven track record implementing trading algorithms and working with distributed systems in fast-paced front-office environments. Experience building transactional systems with More ❯

LL BRING: 5+ years of software development experience in quantitative trading, with deep expertise in Java and/or Python. Proficient in Pythons data science ecosystem (Pandas, NumPy, Scikit-learn), with strong debugging and analytical skills. Proven track record implementing trading algorithms and working with distributed systems in fast-paced front-office environments. Experience building transactional systems with More ❯

or D3.js. • Demonstrated ability to manipulate large financial datasets and time series data and perform calculations with at least one modern programming language like Python (utilizing packages like scikit-learn, pandas, or dask), R (utilizing packages like caret, dplyr, or data.table), or other modern language. • Ability to apply, modify and formulate algorithms and processes to solve computational financial More ❯

LLMs and generative AI. Able to contextualise these techniques in industry settings, such as financial forecasting, operations optimisation, or customer segmentation. Comfortable with key ML frameworks (such as Scikit-learn, TensorFlow, PyTorch, Hugging Face) and data manipulation tools (Pandas, NumPy), as well as version control, containerisation, and ML deployment pipelines. Understands how to apply MLOps principles in production … Strong applied experience in machine learning and/or data science roles Solid understanding of MLOps and production deployment practices Experience with Python and core ML libraries (e.g., Scikit-learn, Pandas, PyTorch, TensorFlow) Familiarity with cloud platforms and data infrastructure (e.g., AWS/GCP/Azure, SQL, ELT tools) Understanding of ethical frameworks, explainability, and governance in AI More ❯

DEPT/AI has a single mission: to make the best work in the industry using AI to enhance everything we do. This role sits within our EMEA Data & AI practice, which has deep expertise in leveraging AI. The team More ❯

Grow with us. We are looking for a Machine Learning Engineer to work along the end-to-end ML lifecycle, alongside our existing Product & Engineering team. About Trudenty: The Trudenty Trust Network provides personalised consumer fraud risk intelligence for fraud More ❯

Collaborating on data strategy and architecture in a fast-moving environment 2+ years' experience in applied Machine Learning Strong Python skills, with familiarity in libraries like PyTorch, TensorFlow, scikit-learn Experience deploying models into production environments Solid grasp of MLOps or data pipelines (e.g., MLflow, Airflow, or similar tools) Previous experience in a start-up or high-growth More ❯

in AI/ML, with a focus on sequential data and complex decision-making Develop novel algorithms and prototypes in Python using frameworks such as PyTorch, TensorFlow, and scikit-learn Mentor junior scientists and contribute to team-wide technical strategy Deliver technical reports, presentations, and research proposals to internal and external stakeholders Collaborate with top UK universities and More ❯

on areas such as robustness, explainability, or uncertainty estimation. Advanced programming and mathematical skills with Python and an experience with the standard Python data science stack (NumPy, pandas, Scikit-learn etc.) The ability to conduct and oversee complex technical research projects. A passion for leading and developing technical teams; adopting a caring attitude towards the personal and professional More ❯

PhD (or equivalent experience) in a relevant discipline Deep knowledge of machine learning and statistical signal processing Strong Python skills and familiarity with frameworks like PyTorch, TensorFlow, and scikit-learn Experience working with time-series, sensor, or RF data Track record of delivering innovative solutions in complex technical domains Please note: Due to the nature of the work More ❯

years' experience in a hands-on data science or advanced analytics role. Proven experience with Microsoft Fabricand Power BIin a production environment. Strong skills in Python (e.g. Pandas, scikit-learn, NumPy) or R. Proficient in SQL and working with relational databases. Experience building and deploying statistical or machine learning models. Experience working in cloud environments, preferably Azure. At More ❯

Required Proven experience as a Data Scientist, ideally in a government, defence, or security environment. Strong programming skills in Python or R, including experience with libraries such as scikit-learn, TensorFlow, or PyTorch. Solid understanding of statistical modelling, machine learning, and data mining techniques. Experience with SQL and working with large-scale databases. Familiarity with data visualisation tools More ❯