76 to 100 of 361 scikit-learn Jobs

Java, Golang, or C++ At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data ...

Java, Golang, or C++ At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data ...

identify opportunities to improve business efficiency through intelligent automation. Skills & Experience Strong Python programming skills with experience using libraries such as Pandas, NumPy, Scikit-learn, XGBoost or LightGBM, and Plotly, Rust, Typescript, Python or Matplotlib. Experience developing machine learning models for prediction, optimisation or classification. Strong SQL skills ...

with modern deep learning frameworks (e.g. PyTorch, TensorFlow), fine-tuning or distillation of LLMs (e.g. GPT, Llama, Claude, Gemini), machine learning libraries (e.g. scikit-learn, XGBoost). Experience with data storage for AI, vector databases, semantic search and knowledge graphs. Actively contributes to open-source AI projects, research ...

with modern deep learning frameworks (e.g. PyTorch, TensorFlow), fine-tuning or distillation of LLMs (e.g. GPT, Llama, Claude, Gemini), machine learning libraries (e.g. scikit-learn, XGBoost). Experience with data storage for AI, vector databases, semantic search and knowledge graphs. Actively contributes to open-source AI projects, research ...

with modern deep learning frameworks (e.g. PyTorch, TensorFlow), fine-tuning or distillation of LLMs (e.g., GPT, Llama, Claude, Gemini), machine learning libraries (e.g. scikit-learn, XGBoost). Experience with data storage for AI, vector databases, semantic search, and knowledge graphs. Contributions to open-source AI projects or research ...

5+ years of applied experience building production Python systems, including web/API services (Flask or FastAPI) and the ML/NLP ecosystem (scikit-learn, pandas, NumPy). Demonstrated experience taking machine learning models from prototype to production - training, packaging, deployment, monitoring, retraining, and decommissioning - in real-world ...

lifecycle expertise: feature engineering, model training, evaluation and production deployment, including MLOps, monitoring and drift detection. Practical knowledge of ML frameworks (e.g. scikit-learn, PyTorch, XGBoost) and cloud-native ML services (SageMaker, Azure ML, Vertex AI). Software Engineering: Production-grade Python services (FastAPI, AWS Lambda, event-driven ...

managing a data science team. Proficiency in programming languages such as Python, R, and SQL.Strong experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).Expertise in data manipulation, analysis, and visualization tools (e.g., Pandas, Matplotlib, Tableau).Experience with cloud platforms (e.g., AWS, GCP, Azure) and distributed computing ...

lifecycle expertise: feature engineering, model training, evaluation and production deployment, including MLOps, monitoring and drift detection. Practical knowledge of ML frameworks (e.g. scikit-learn, PyTorch, XGBoost) and cloud-native ML services (SageMaker, Azure ML, Vertex AI). Software Engineering: Production-grade Python services (FastAPI, AWS Lambda, event-driven ...

Hands‐on experience training, deploying, and maintaining machine learning models in production environments Proficiency in Python and relevant AI/ML libraries (e.g. scikit‐learn, TensorFlow, PyTorch) Experience with MLOps practices and tools for managing the machine learning lifecycle Experience building and deploying Generative AI applications, including familiarity ...

experience on Gen AI implementations Experience on Langchain, Vector DB, Embeddings or related frameworks Experience on AI/ML model implementations using scikit learn, Tensor flow etc., Experience with Chat, IVR, Banking will be plus Google Cloud (GCP) knowledgeAbout NTT DATANTT DATA is a $30 billion business ...

mixed integer programming, heuristics) Fluent in Python (required) and other programming languages (preferred) with strong skills in applying DS, ML, and OR packages (scikit‐learn, pandas, numpy, gurobi, etc.) to solve real‐life problems and visualise the outcomes (e.g., seaborn) Proficient in working with cloud platforms (AWS preferred ...

happy to discuss further. Preferred Qualifications Experience with Vue or other similar JavaScript framework Experience with simple NLP methods using Gensim and scikit-learn Knowledge of testing methodologies and an uncompromising ethic around automated testing Experience with microservices architecture Perks Coming on board in the early stages ...

producing high-quality work Collaborative team player, committed to continuous improvement Desirable: Extensive experience with Python and machine learning frameworks (TensorFlow, PyTorch, scikit-learn) Experience in developing and deploying machine learning models in production environments Experience with data visualization tools (Tableau, Power BI, or similar) Familiarity with cloud ...

product managers Contribute to a culture of continuous improvement, knowledge sharing, and technical excellence Required Skills & Qualifications Strong proficiency in Python (NumPy, Pandas, Scikit-learn, or similar) Experience building data pipelines and working with structured and unstructured data Solid understanding of SQL and relational and non-relational databases ...

experience training, deploying, and maintaining machine learning models in production environments Proficiency in Python and relevant AI/ML libraries (such as scikit-learn, TensorFlow, PyTorch) Experience with MLOps practices and tools for managing the machine learning lifecycle Experience building and deploying Generative AI applications, including familiarity with ...

product managers Contribute to a culture of continuous improvement, knowledge sharing, and technical excellence Required Skills & Qualifications Strong proficiency in Python (NumPy, Pandas, Scikit-learn, or similar) Experience with React (hooks, state management, component architecture) Experience building data pipelines and working with structured and unstructured data Solid understanding ...

provider LLM APIs or integration with the latest Machine Learning models Collaborate with research teams on innovative machine learning experiments Tech stack: Python, scikit-learn, TensorFlow, PyTorch, Java, Angular, AngularJS Data Consumption: build the experience that makes data accessible and actionable for everyone. Enhance our collaborative Workspaces ...

Not. Classic ML Is Necessary. It Is No Longer Sufficient. Your last serious data work used older pandas flows, on-prem SQL, and scikit-learn only. Postings now mention Databricks, Snowflake, PyTorch, LLMs, GenAI, and MLOps. You apply anyway. You do not get interviews, or you get them ...

analysisHands-on experience training, deploying, and maintaining machine learning models in production environmentsProficiency in Python and relevant AI/ML libraries (such as scikit-learn, TensorFlow, PyTorch)Experience with MLOps practices and tools for managing the machine learning lifecycleExperience building and deploying Generative AI applications, including familiarity with ...

experience training, deploying, and maintaining machine learning models in production environments Proficiency in Python and relevant AI/ML libraries (such as scikit-learn, TensorFlow, PyTorch) Experience with MLOps practices and tools for managing the machine learning lifecycle Experience building and deploying Generative AI applications, including familiarity with ...

experience with modern deep learning frameworks (e.g.PyTorch, TensorFlow),fine-tuning or distillation of LLMs (e.g. GPT, Llama, Claude, Gemini), machine learning libraries (e.g. scikit-learn,XGBoost). Experience with data storage for AI, vector databases, semanticsearchand knowledge graphs. Actively contributes to open-source AI projects, researchpublicationsand industry events ...

experience with modern deep learning frameworks (e.g.PyTorch, TensorFlow), fine-tuning or distillation of LLMs (e.g., GPT, Llama, Claude, Gemini), machine learning libraries (e.g. scikit-learn,XGBoost). Experience with data storage for AI, vector databases, semanticsearch,and knowledge graphs. Contributions to open-source AI projects or research publications. ...

predictive modelling, classification, regression, optimisation or recommendation systems Strong proficiency in Python and open-source data libraries such as Pandas, NumPy and Scikit-learn A solid grounding in statistical methodologies, along with data extraction, manipulation and feature engineering techniques Experience with Spark, agile delivery methods and CI/ ...