1 to 25 of 111 scikit-learn Jobs

Master's degree in a related field required. Advanced experience developing and deploying machine learning models using Python and modern ML frameworks (e.g., Scikitlearn, PyTorch, TensorFlow). Strong applied expertise across core ML techniques, including regression, tree based models, clustering, deep learning, and NLP. Familiarity with generative AI and LLMs ...

mentor engineers and scientists, lead applied research initiatives What You'll Bring Technical Expertise: Strong Python skills with the ML stack: NumPy, pandas, scikit-learn Hands-on experience with at least one deep learning framework (PyTorch, TensorFlow, JAX) Solid grounding in core ML—supervised, unsupervised, evaluation, regularisation, statistics ...

detection. Provide mentorship and technical guidance to junior AI Scientists. Skills: Strong 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, leading LLM libraries such as Hugging ...

detection.* Provide mentorship and technical guidance to junior AI Scientists**Skills*** Strong 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 ...

Experience Experience building and deploying AI or Machine Learning solutions in a commercial environment Strong Python and SQL skills Experience using TensorFlow, PyTorch, Scikit-learn or similar frameworks Strong understanding of machine learning algorithms, deep learning architectures and model deployment practices Experience with Azure, AWS or GCP cloud ...

machine learning, including coursework or practical work with NLP or LLMs Proficiency in Python for data analysis (Pandas, NumPy) and ML model development (scikit-learn, PyTorch) Experience programming in Java and C++ Strong understanding of Linux, including command-line usage, system navigation, and scripting Familiarity with LLM concepts ...

related field Proven experience in machine learning, deep learning, or AI engineering Proficiency in Python and ML frameworks such as TensorFlow, PyTorch, or scikit-learn Experience with NLP, LLMs, or generative AI tools (e.g., OpenAI, Hugging Face) Familiarity with cloud platforms (AWS, Azure, or GCP) and MLOps practices ...

data science or machine learning, with a strong track record of delivering impactful solutions. Proficiency in Python and ML frameworks such as scikit-learn, XGBoost, PyTorch, TensorFlow, or similar. Experience with statistical modeling, time series forecasting, supervised and unsupervised learning, and optimization techniques. Experience with generative AI principles. ...

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 ...

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 ...

/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. ...

Proficiency in SQL including strong knowledge of database structure and efficiency Proficiency in Git Proficiency in AI/ML frameworks: Huggingface, Torch, TensorFlow, Scikit‐Learn, and Spacy Experience in MLOps platforms: MLFlow, dbt, Docker, Kubernetes Experience with cloud environments such as AWS Technical Concept Requirements Experience ...

learning Exposure to machine learning models and corresponding statistics like K‐means, Bayesian, Clustering Strong technical skills with Python along with NumPy, Pandas, Scikit‐Learn Machine learning experience -> predictive and prescriptive modelling Data wrangling and data cleansing experience Strong analytical skills Any experience with Node.JS would be beneficial. ...

Docker and containerised application experience Infrastructure as code experience, ideally Terraform or CloudFormation Experience with SQL, PySpark, Databricks or AWS Glue Exposure to Scikit‐learn, PyTorch, LightGBM or similar libraries An understanding of LLMs, multimodal models or generative AI applications Deep commercial LLM experience is not essential. ...

Python and SQL, with experience in data manipulation, model development, and analytical workflows. Hands‐on experience with machine learning frameworks such as scikit‐learn, TensorFlow, PyTorch, or similar. Strong experience with cloud platforms (AWS, Azure, or GCP) and building cloud‐native systems. Experience with modern data platforms such ...

science practices tooling governance Essential Skills for the Data Scientist: Strong experience in data science using Python with libraries such as Pandas NumPy scikit-learn or similar Solid grounding in statistics probability machine learning techniques Proven experience working within cloud environments such as AWS Azure or GCP Experience ...

such as AWS, Azure, or Google Cloud Platform 4+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 3+ years of experience developing performant, resilient, and maintainable code 3+ 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 ...

such as AWS, Azure, or Google Cloud Platform 4+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 3+ years of experience developing performant, resilient, and maintainable code 3+ 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 ...

such as AWS, Azure, or Google Cloud Platform 4+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 3+ years of experience developing performant, resilient, and maintainable code 3+ 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 ...

Data Science, Mathematics, Computer Science, or a related field. Strong programming skills in Python or R, with experience using frameworks such as Scikit-learn, PyTorch, or TensorFlow. Experience with cloud platforms or distributed computing (GCP preferred, but AWS or Azure also welcome). Exposure to neural networks ...

Data Engineering, or Software Engineering roles Strong production Python experience Hands‐on experience training and serving ML models Familiarity with PyTorch, TensorFlow, or scikit‐learn Strong working knowledge of Docker, Linux, Git, and cloud platforms (AWS, Azure, or similar) Experience deploying systems you’ve helped design Excellent communication ...