1 to 25 of 547 scikit-learn Jobs

audiences, advocating for interpretability and audit best practices.Experience working with structured and unstructured datasets.Proficient in Python, leveraging key data science libraries (NumPy, Pandas, scikit-learn) and applying object-oriented programming principles to develop efficient, scalable solutionsHands-on experience experimenting with Generative AI (e.g. LangChain, Hugging Face, LlamaIndex).Experience ...

Bedrock, SageMaker, Lambda, DynamoDB). Exposure to the Python data and ML ecosystem (e.g., Pandas, NumPy, and libraries such as PyTorch, TensorFlow, or Scikit-learn). Familiarity with RESTful APIs, web services, and third-party or system integrations. Understanding of AI model and prompt evaluation, monitoring, governance, security ...

/C++.Experience with machine-learning, deep-learning, computer-vision, and generative-AI frameworks.Proficiency in ML modeling frameworks and libraries such as scikit-learn, TensorFlow, Keras, PyTorch, OpenCV, YOLO, Detectron, Hugging Face, or equivalent with natural-language-processing techniques, including text classification and language developing and evaluating image-analysis ...

/ML development, with practical experience across model development, testing and deployment. Experience with machine learning frameworks and libraries such as PyTorch, TensorFlow, scikit-learn, XGBoost or equivalent. Practical knowledge of Generative AI techniques, including large language models, prompt engineering, retrieval-augmented generation, model evaluation and responsible ...

/ML development, with practical experience across model development, testing and deployment. Experience with machine learning frameworks and libraries such as PyTorch, TensorFlow, scikit-learn, XGBoost or equivalent. Practical knowledge of Generative AI techniques, including large language models, prompt engineering, retrieval-augmented generation, model evaluation and responsible ...

/ML development, with practical experience across model development, testing and deployment. Experience with machine learning frameworks and libraries such as PyTorch, TensorFlow, scikit-learn, XGBoost or equivalent. Practical knowledge of Generative AI techniques, including large language models, prompt engineering, retrieval-augmented generation, model evaluation and responsible ...

/ML development, with practical experience across model development, testing and deployment. Experience with machine learning frameworks and libraries such as PyTorch, TensorFlow, scikit-learn, XGBoost or equivalent. Practical knowledge of Generative AI techniques, including large language models, prompt engineering, retrieval-augmented generation, model evaluation and responsible ...

/ML development, with practical experience across model development, testing and deployment. Experience with machine learning frameworks and libraries such as PyTorch, TensorFlow, scikit-learn, XGBoost or equivalent. Practical knowledge of Generative AI techniques, including large language models, prompt engineering, retrieval-augmented generation, model evaluation and responsible ...

/ML development, with practical experience across model development, testing and deployment. Experience with machine learning frameworks and libraries such as PyTorch, TensorFlow, scikit-learn, XGBoost or equivalent. Practical knowledge of Generative AI techniques, including large language models, prompt engineering, retrieval-augmented generation, model evaluation and responsible ...

supervised learning, unsupervised learning, statistical modelling, feature engineering, validation, model evaluation and optimisation. · Hands-on experience with Python-based machine learning libraries, especially Scikit-Learn and at least one of XGBoost, LightGBM, TensorFlow or PyTorch. · Experience developing models beyond exploratory analysis into reusable, documented and testable assets, ideally ...

both statistically and commercially credible. Strong Python or R and SQL skills (joins, CTEs, window functions), with libraries such as pandas, NumPy, scikit-learn, statsmodels, or SciPy — and explainability tools like SHAP. Fluent in commercial concepts (ROI, ROAS, incremental revenue, margin, market share) and comfortable partnering directly with ...

problems into measurable analytical outcomes.* Experience taking models from development into production environments.### Technical Skills* Python and associated data science ecosystem (Pandas, NumPy, Scikit-learn).* Machine learning techniques including classification, regression, clustering and anomaly detection.* Experience with Generative AI, LLMs, RAG architectures or agent-based AI solutions. ...

used for AI and data engineering, with hands-on experience building production-grade solutions.Experience with machine learning frameworks and tools (e.g., PyTorch, TensorFlow, scikit-learn) and practical implementation of model development and deployment.Working knowledge of Generative AI, including large language models, prompt engineering, retrieval-augmented generation and evaluation ...

used for AI and data engineering, with hands-on experience building production-grade solutions.Experience with machine learning frameworks and tools (e.g., PyTorch, TensorFlow, scikit-learn) and practical implementation of model development and deployment.Working knowledge of Generative AI, including large language models, prompt engineering, retrieval-augmented generation and evaluation ...

used for AI and data engineering, with hands-on experience building production-grade solutions.Experience with machine learning frameworks and tools (e.g., PyTorch, TensorFlow, scikit-learn) and practical implementation of model development and deployment.Working knowledge of Generative AI, including large language models, prompt engineering, retrieval-augmented generation and evaluation ...

used for AI and data engineering, with hands-on experience building production-grade solutions.Experience with machine learning frameworks and tools (e.g., PyTorch, TensorFlow, scikit-learn) and practical implementation of model development and deployment.Working knowledge of Generative AI, including large language models, prompt engineering, retrieval-augmented generation and evaluation ...

architectures like CNNs, RNNs, LSTM, and GANs and ability to apply to real world data sets and problems. Proficiency in ML Modeling - Scikit-Learn, Tensorflow, Keras, Pytorch. Proficiency in NLP Tools SpaCy, ThinC, Gensim. Knowledge of Gen-AI Tools Hugging Face models, OpenAI models, Grok. General competency ...

with hands-on experience developing, training, and deploying machine learning models.Practical experience with leading AI/ML frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn, XGBoost), including model selection, tuning, and evaluation.Experience implementing end-to-end machine learning workflows, including data preprocessing, feature engineering, model development, validation ...

with hands-on experience developing, training, and deploying machine learning models.Practical experience with leading AI/ML frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn, XGBoost), including model selection, tuning, and evaluation.Experience implementing end-to-end machine learning workflows, including data preprocessing, feature engineering, model development, validation ...

with hands-on experience developing, training, and deploying machine learning models.Practical experience with leading AI/ML frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn, XGBoost), including model selection, tuning, and evaluation.Experience implementing end-to-end machine learning workflows, including data preprocessing, feature engineering, model development, validation ...

with hands-on experience developing, training, and deploying machine learning models.Practical experience with leading AI/ML frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn, XGBoost), including model selection, tuning, and evaluation.Experience implementing end-to-end machine learning workflows, including data preprocessing, feature engineering, model development, validation ...

with hands-on experience developing, training, and deploying machine learning models.Practical experience with leading AI/ML frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn, XGBoost), including model selection, tuning, and evaluation.Experience implementing end-to-end machine learning workflows, including data preprocessing, feature engineering, model development, validation ...

with hands-on experience developing, training, and deploying machine learning models.Practical experience with leading AI/ML frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn, XGBoost), including model selection, tuning, and evaluation.Experience implementing end-to-end machine learning workflows, including data preprocessing, feature engineering, model development, validation ...

score, and hallucination detection.Provide mentorship and technical guidance to junior AI ScientistsSkillsStrong proficiency in Python and experience with frameworks such as NumPy, Pandas, Scikit-learn, and modern Generative AI libraries (e.g., LangChain, LlamaIndex, Azure AI Foundry).Hands-on experience with PyTorch, and leading LLM libraries such as Hugging ...

programming languages such as Java, C#, C++, or JavaScript/TypeScript. Experience working with AI or machine learning frameworks such as PyTorch, TensorFlow, Scikit-learn, Hugging Face, LangChain, OpenAI APIs, Azure OpenAI, Amazon Bedrock, or similar technologies is preferred. Working knowledge of cloud computing platforms (AWS, Azure ...