76 to 100 of 424 scikit-learn Jobs

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 ...

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 ...

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 ...

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. ...

context and memory management, and interoperability protocols such as MCP Experience with machine learning frameworks and data science packages such as PyTorch, TensorFlow, scikit-learn, NumPy, pandas, SciPy, and statsmodels Experience deploying to AWS, including services such as SageMaker and Bedrock, and operating production large language model ...

frameworks, context and memory management, and interoperability protocols such as MCPExperience with machine learning frameworks and data science packages such as PyTorch, TensorFlow, scikit-learn, NumPy, pandas, SciPy, and statsmodelsExperience deploying to AWS, including services such as SageMaker and Bedrock, and operating production large language model and machine ...

leading ML/AI technical initiatives across multiple teams Strong experience with cloud platforms (AWS, Azure, GCP) Experience with ML frameworks (PyTorch, TensorFlow, scikit-learn) and Gen AI/Agentic frameworks (LangGraph, LangChain, VectorDBs, RAG) Understanding of responsible AI practices, including guardrails, hallucination mitigation, and output quality management ...

leading ML/AI technical initiatives across multiple teamsStrong experience with cloud platforms (AWS, Azure, GCP)Experience with ML frameworks (PyTorch, TensorFlow, scikit-learn) and Gen AI/Agentic frameworks (LangGraph, LangChain, VectorDBs, RAG)Understanding of responsible AI practices, including guardrails, hallucination mitigation, and output quality management ...

object-oriented design and software engineering fundamentals: version control, code review, automated testing, dependency and environment management. Machine learning across the standard toolkit (scikit learn, pandas, NumPy, statsmodels or equivalents), with sound judgement about model selection, validation and the limits of what the data supports. MLOps ...

context and memory management, and interoperability protocols such as MCP Experience with machine learning frameworks and data science packages such as PyTorch, TensorFlow, scikit‐learn, NumPy, pandas, SciPy, and statsmodels Experience deploying to AWS, including services such as SageMaker and Bedrock, and operating production large language model ...

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 ...

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). Architecture and delivery of scalable cloud data and AI platforms ...

Python (Pandas, NumPy, etc.). Proficiency in SQL for data querying and transformation. Hands-on experience with Machine Learning techniques and frameworks (e.g., scikit-learn, TensorFlow, PyTorch). Experience working with data manipulation and large datasets. Proven experience developing and maintaining production-level codebases . Experience with ...

bottlenecks to strategic AI solutions. Software/Data Engineering: Python proficiency, API design, SQL, data integration, and ML/AI libraries (PyTorch, TensorFlow, scikit-learn, XGBoost, Hugging Face Transformers). Agentic AI Systems: Hands-on experience with agentic AI setups including LLM orchestration, tool use/function calling ...

client projects Requirements 5+ years of experience in machine learning engineering or applied ML research Strong proficiency in Python, PyTorch or TensorFlow, and Scikit-learn Experience deploying ML models at scale using Docker, Kubernetes, or serverless Deep understanding of ML fundamentals: optimisation, regularisation, evaluation metrics Experience with cloud ...

similar languages.Experience building data pipelines and working with structured and unstructured data.Familiarity with Generative AI and/or machine learning frameworks (e.g. scikit-learn, TensorFlow, PyTorch, Langchain) is desirable.Experience with cloud data platforms, data warehouses, or big data technologies is an advantage.Strong analytical and problem-solving skills, with ...

production-ready data pipelines that feed ML models 3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 2+ years of experience developing performant, resilient, and maintainable code 2+ years of experience with data gathering ...

production-ready data pipelines that feed ML models 3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 2+ years of experience developing performant, resilient, and maintainable code 2+ years of experience with data gathering ...

production-ready data pipelines that feed ML models 3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 2+ years of experience developing performant, resilient, and maintainable code 2+ years of experience with data gathering ...

/ML techniques to text, audio, imagery, video, geospatial, graph or multimodal data.Developing solutions using machine learning frameworks such as PyTorch, TensorFlow, scikit-learn or Hugging Face.Using cloud-based data science and machine learning services across AWS, Azure, GCP or equivalent platforms.Developing high-quality, maintainable code and working ...

/ML techniques to text, audio, imagery, video, geospatial, graph or multimodal data.Developing solutions using machine learning frameworks such as PyTorch, TensorFlow, scikit-learn or Hugging Face.Using cloud-based data science and machine learning services across AWS, Azure, GCP or equivalent platforms.Developing high-quality, maintainable code and working ...

/ML techniques to text, audio, imagery, video, geospatial, graph or multimodal data.Developing solutions using machine learning frameworks such as PyTorch, TensorFlow, scikit-learn or Hugging Face.Using cloud-based data science and machine learning services across AWS, Azure, GCP or equivalent platforms.Developing high-quality, maintainable code and working ...

similar languagesExperience building data pipelines and working with structured and unstructured data.Familiarity with Generative AI and/or machine learning frameworks (e.g. scikit-learn, TensorFlow, PyTorch, Langchain) is desirable. Experience with cloud data platforms, data warehouses, or big data technologies is an advantage. Strong analytical and problem-solving ...

similar languagesExperience building data pipelines and working with structured and unstructured data.Familiarity with Generative AI and/or machine learning frameworks (e.g. scikit-learn, TensorFlow, PyTorch, Langchain) is desirable. Experience with cloud data platforms, data warehouses, or big data technologies is an advantage. Strong analytical and problem-solving ...