1 to 25 of 157 Permanent scikit-learn Jobs

mentorship to junior engineers Required Experience & Skills Core Technical Skills Strong hands‐on experience with Python , and at least one of: TensorFlow, PyTorch, scikit‐learn Practical experience with LLMs and Generative AI , including: Prompt engineering Retrieval‐Augmented Generation (RAG) Agentic workflows Experience deploying AI on cloud platforms (Azure ...

stack products Strong backend (Node.js, Python/Flask, FastAPI) and frontend (React, Next.js, Vue) fundamentals ML/data science proficiency: Python, SQL, pandas, scikit-learn, PyTorch/TensorFlow Experience with cloud platforms (AWS, GCP, Azure) and containerisation (Docker, Kubernetes) Proven ability to build data-secure, privacy-compliant infrastructure ...

GenAI: Experience with LLM APIs and Context Engineering (constructing prompts, managing context windows, evaluating behaviour). Engineering & Stack: Python: Expert level (Pandas, NumPy, Scikit-Learn). Data Engineering: Strong SQL skills and experience building data pipelines. Experience: Education: Degree in a quantitative field (Statistics, Mathematics, Computer Science, etc. ...

versioning, monitoring, and retraining Mandatory Skills • Python programming, with exposure to Java considered an advantage • Machine learning frameworks such as TensorFlow, PyTorch, and Scikit-learn • Data handling using Pandas, NumPy, and SQL • Supervised and unsupervised learning with deep learning fundamentals • Model deployment using REST APIs, Flask or FastAPI ...

years of experience in Artificial Intelligence/Machine Learning . Strong programming experience in Python . Experience with TensorFlow, PyTorch, or Scikit-learn . Knowledge of data processing tools such as Pandas, NumPy . Experience with NLP, Computer Vision, or Predictive Analytics . Understanding of cloud platforms like ...

Machine Learning deployments on AWS, Azure or GCP Extensive hands-on data science experience, leveraging machine learning and data science tools (i.e., pandas, scikit-learn, PyTorch, etc.) Experience with DevOps tools: Kubernetes, Docker, Terraform, CI/CD Pipelines, GitHub/GitLab, GitOps, GitHub Actions, Jira, Jenkins, CircleCI, Datadog ...

Machine Learning deployments on AWS, Azure or GCP Extensive hands-on data science experience, leveraging machine learning and data science tools (i.e., pandas, scikit-learn, PyTorch, etc.) Experience with DevOps tools: Kubernetes, Docker, Terraform, CI/CD Pipelines, GitHub/GitLab, GitOps, GitHub Actions, Jira, Jenkins, CircleCI, Datadog ...

will have experience in many of the following: Hands-on experience developing and deploying ML models in Python using frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow Strong experience with AWS ML services (SageMaker, Lambda, S3) in production environments Strong experiment design skills: hypothesis formulation, A/ ...

learning technologies and best practices Skills and Experience • Strong programming skills in Python • Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn • Experience working with SQL and large datasets • Familiarity with data pipelines, feature engineering, and model optimisation • Understanding of MLOps practices, model deployment ...

Machine Learning deployments on AWS, Azure or GCP Extensive hands-on data science experience, leveraging machine learning and data science tools (i.e., pandas, scikit-learn, PyTorch, etc.) Experience with DevOps tools: Kubernetes, Docker, Terraform, CI/CD Pipelines, GitHub/GitLab, GitOps, GitHub Actions, Jira, Jenkins, CircleCI, Datadog ...

Python (or similar experience with a desire to develop Python skills) Familiarity with essential data science tools and libraries (e.g. NumPy, Pandas, Scikit-Learn) and machine learning (e.g. PyTorch, Tensorflow, Huggingface, LangChain, LiteLLM). A high level of competence in applied maths, statistics and scientific methods. Clear written ...

Python (or similar experience with a desire to develop Python skills) Familiarity with essential data science tools and libraries (e.g. NumPy, Pandas, Scikit-Learn) and machine learning (e.g. PyTorch, Tensorflow, Huggingface, LangChain, LiteLLM). A high level of competence in applied maths, statistics and scientific methods. Clear written ...

Python (or similar experience with a desire to develop Python skills) Familiarity with essential data science tools and libraries (e.g. NumPy, Pandas, Scikit-Learn) and machine learning (e.g. PyTorch, Tensorflow, Huggingface, LangChain, LiteLLM). A high level of competence in applied maths, statistics and scientific methods. Clear written ...

Python (or similar experience with a desire to develop Python skills) Familiarity with essential data science tools and libraries (e.g. NumPy, Pandas, Scikit-Learn) and machine learning (e.g. PyTorch, Tensorflow, Huggingface, LangChain, LiteLLM). A high level of competence in applied maths, statistics and scientific methods. Clear written ...

Python (or similar experience with a desire to develop Python skills) Familiarity with essential data science tools and libraries (e.g. NumPy, Pandas, Scikit-Learn) and machine learning (e.g. PyTorch, Tensorflow, Huggingface, LangChain, LiteLLM). A high level of competence in applied maths, statistics and scientific methods. Clear written ...

Python (or similar experience with a desire to develop Python skills) Familiarity with essential data science tools and libraries (e.g. NumPy, Pandas, Scikit-Learn) and machine learning (e.g. PyTorch, Tensorflow, Huggingface, LangChain, LiteLLM). A high level of competence in applied maths, statistics and scientific methods. Clear written ...

enterprise environments Deep understanding of algorithm selection, model complexity trade-offs, and overfitting/underfitting dynamics Strong proficiency in Python and ML ecosystems (scikit-learn, pandas, NumPy) Experience with deep learning frameworks (PyTorch or TensorFlow) Practical knowledge of deep learning architectures (CNNs, RNNs, Transformers) and when to apply ...

data science expertise Machine learning and AI delivery Generative AI/LLM experience Strong Python skills and familiarity with core libraries (pandas, NumPy, scikit‐learn) Deep learning and NLP stacks (PyTorch, HuggingFace Transformers) MLOps and model operationalization Responsible AI awareness Additional Requirements: Security clearance (SC/BPSS ...

enterprise environments Deep understanding of algorithm selection, model complexity trade-offs, and overfitting/underfitting dynamics Strong proficiency in Python and ML ecosystems (scikit-learn, pandas, NumPy) Experience with deep learning frameworks (PyTorch or TensorFlow) Practical knowledge of deep learning architectures (CNNs, RNNs, Transformers) and when to apply ...

delivering ML/AI solutions into production environments Strong Python expertise and experience with modern AI/ML frameworks such as: PyTorch TensorFlow scikit-learn NumPy Pandas Hands-on experience with Generative AI, agentic AI systems, and AI testing frameworks Strong communication skills and a passion for clear ...

university is a great indicator, though it's your depth of applied expertise that matters most. Technically, you bring: Python fluency (NumPy, Pandas, Scikit-Learn, PyTorch) and solid TypeScript/API skills Hands-on experience with LLMs prompt engineering, evaluation, RAG architectures, safety considerations Cloud-native development ...

years of hands-on experience in data science, machine learning, or applied statistics. Strong Python skills with experience in ML frameworks such as scikit-learn, PyTorch, TensorFlow, or similar. Solid grounding in statistics — hypothesis testing, regression, correlation analysis, and experimental design. Experience with SQL and data manipulation ...

full-cycle AI software and deploying production-ready solutions. Strong proficiency in Python and core AI/data science libraries, such as: PyTorch, TensorFlow, ScikitLearn, Keras, NumPy, Pandas PyTorch Geometric, JAX, XGBoost, OpenCV Transformers, LangChain, Pinecone Hands-on experience with cloud computing systems for training, optimising, and deploying models. Strong ...

years’ Data Science/Analytics experience within gambling or iGaming Experience working with sportsbook, casino, or betting datasets 🐍 Strong Python (Pandas, NumPy, Scikit-learn) 🗄️ Advanced SQL and large dataset querying 📊 Statistical modelling & machine learning Player behaviour or betting analytics exposure 💬 Strong stakeholder communication skills ⭐ Desirable Skills Odds modelling ...

Science, Artificial Intelligence, Mathematics, Data Science or similar Strong programming skills in Python Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn Experience working with large datasets and building data pipelines Knowledge of cloud platforms such as AWS, GCP, or Azure Experience developing and deploying ...