1 to 25 of 185 scikit-learn Jobs

Conversational AI development Model training, testing and evaluation Prompt Engineering and AI workflow optimisation Programming & Frameworks Strong Python development skills PyTorch TensorFlow Scikit-Learn LangChain LangGraph Hugging Face FastAPI REST APIs Data Technologies SQL NoSQL Databases Data Modelling ETL Development Data Pipeline Engineering Vector Databases such as Pinecone ...

experience with minimum of 2 years of required AI tool working experience Programming: Python (preferred), Java, or Scala ML Frameworks: TensorFlow, PyTorch, Scikit-learn AI/GenAI: prompt engineering (preferred), Claude CLI/Code(preferred), LLMs(preferred) Hugging Face, OpenAI APIs Data Tools (Optional): Pandas, NumPy, Spark APIs ...

C#/.NET. Experience building and deploying production ML systems and APIs. Hands-on knowledge of ML frameworks such as TensorFlow, PyTorch, scikit-learn, or similar. Experience with cloud platforms and modern data infrastructure (AWS preferred). Familiarity with Docker, CI/CD pipelines, and scalable deployment practices. ...

Looking For: Essential Skills & Experience Proven experience solving complex, real-world problems using data science and analytics Strong Python skills (pandas, numpy, scikit-learn) with a solid grounding in probability and statistics Deep understanding of machine learning methods and their practical applicati on.Experience delivering multiple ...

strategic goals, ensuring measurable business outcomes. What you will bring: Commercial experience building AI/ML solutions with Python Expertise in TensorFlow, PyTorch, Scikit-learn, Transformers, LLMs, and techniques such as fine-tuning and RAG. Experience deploying AI solutions in AWS, Azure, or GCP environments. Strong MLOps knowledge ...

transferable Proven experience as a Machine Learning Engineer within central government or regulated environments Strong programming skills in Python (e.g. Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch) Experience building and deploying ML models into production environments Strong knowledge of cloud platforms, particularly: Azure (ML Studio, Azure ML, Data Factory ...

speech recognition and conversational AI solutions Fine-tuning and optimisation of AI models Model evaluation, monitoring and governance Technologies Python (essential) PyTorch TensorFlow Scikit-Learn LangChain LangGraph Hugging Face Vector Databases (Pinecone, Weaviate, ChromaDB or similar) FastAPI REST APIs Cloud & Infrastructure AWS (essential) Bedrock SageMaker Lambda ECS/ ...

datasets (e.g., Spark, Airflow, or similar tools) Hands-on experience with cloud platforms (AWS, Azure, or GCP) Familiarity with machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch) Experience with data visualization and BI tools Strong problem-solving skills and ability to communicate technical concepts to non-technical stakeholders ...

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. ...

/ML Requirements Basic to intermediate understanding of Machine Learning/Deep Learning concepts Experience using frameworks like TensorFlow/PyTorch/scikit-learn Ability to integrate pretrained models into Back End systems Familiarity with model deployment tools (eg, Docker, APIs, model serving) Preferred Qualifications Competitive programming experience ...

Python and its core data science libraries: Pandas, NumPy, and SciPy . Machine Learning: Deep, practical experience with popular ML frameworks and libraries: scikit-learn, TensorFlow, or PyTorch . Statistics & Math: Strong foundation in statistical modeling , probability, hypothesis testing, regression analysis, and multivariate calculus/linear algebra ...

Skills: 5+ years of experience in ML Engineering or Applied Machine Learning. Strong Python skills and hands-on experience with ML libraries (e.g., scikit-learn, XGBoost, PyTorch, TensorFlow). Proficient with Databricks, MLflow, and PySpark. Solid understanding of model lifecycle and MLOps practices. Experience with AWS-based data ...

Skills: 5+ years of experience in ML Engineering or Applied Machine Learning. Strong Python skills and hands-on experience with ML libraries (e.g., scikit-learn, XGBoost, PyTorch, TensorFlow). Proficient with Databricks, MLflow, and PySpark. Solid understanding of model lifecycle and MLOps practices. Experience with AWS-based data ...

Skills: 5+ years of experience in ML Engineering or Applied Machine Learning. Strong Python skills and hands-on experience with ML libraries (e.g., scikit-learn, XGBoost, PyTorch, TensorFlow). Proficient with Databricks, MLflow, and PySpark. Solid understanding of model lifecycle and MLOps practices. Experience with AWS-based data ...

Skills: 5+ years of experience in ML Engineering or Applied Machine Learning. Strong Python skills and hands-on experience with ML libraries (e.g., scikit-learn, XGBoost, PyTorch, TensorFlow). Proficient with Databricks, MLflow, and PySpark. Solid understanding of model lifecycle and MLOps practices. Experience with AWS-based data ...

Skills: 5+ years of experience in ML Engineering or Applied Machine Learning. Strong Python skills and hands-on experience with ML libraries (e.g., scikit-learn, XGBoost, PyTorch, TensorFlow). Proficient with Databricks, MLflow, and PySpark. Solid understanding of model lifecycle and MLOps practices. Experience with AWS-based data ...

Skills: 5+ years of experience in ML Engineering or Applied Machine Learning. Strong Python skills and hands-on experience with ML libraries (e.g., scikit-learn, XGBoost, PyTorch, TensorFlow). Proficient with Databricks, MLflow, and PySpark. Solid understanding of model lifecycle and MLOps practices. Experience with AWS-based data ...

Skills: 5+ years of experience in ML Engineering or Applied Machine Learning. Strong Python skills and hands-on experience with ML libraries (e.g., scikit-learn, XGBoost, PyTorch, TensorFlow). Proficient with Databricks, MLflow, and PySpark. Solid understanding of model lifecycle and MLOps practices. Experience with AWS-based data ...

Skills: 5+ years of experience in ML Engineering or Applied Machine Learning. Strong Python skills and hands-on experience with ML libraries (e.g., scikit-learn, XGBoost, PyTorch, TensorFlow). Proficient with Databricks, MLflow, and PySpark. Solid understanding of model lifecycle and MLOps practices. Experience with AWS-based data ...

Skills: 5+ years of experience in ML Engineering or Applied Machine Learning. Strong Python skills and hands-on experience with ML libraries (e.g., scikit-learn, XGBoost, PyTorch, TensorFlow). Proficient with Databricks, MLflow, and PySpark. Solid understanding of model lifecycle and MLOps practices. Experience with AWS-based data ...

Skills: 5+ years of experience in ML Engineering or Applied Machine Learning. Strong Python skills and hands-on experience with ML libraries (e.g., scikit-learn, XGBoost, PyTorch, TensorFlow). Proficient with Databricks, MLflow, and PySpark. Solid understanding of model lifecycle and MLOps practices. Experience with AWS-based data ...

Skills: 5+ years of experience in ML Engineering or Applied Machine Learning. Strong Python skills and hands-on experience with ML libraries (e.g., scikit-learn, XGBoost, PyTorch, TensorFlow). Proficient with Databricks, MLflow, and PySpark. Solid understanding of model lifecycle and MLOps practices. Experience with AWS-based data ...

Skills: 5+ years of experience in ML Engineering or Applied Machine Learning. Strong Python skills and hands-on experience with ML libraries (e.g., scikit-learn, XGBoost, PyTorch, TensorFlow). Proficient with Databricks, MLflow, and PySpark. Solid understanding of model lifecycle and MLOps practices. Experience with AWS-based data ...

Skills: 5+ years of experience in ML Engineering or Applied Machine Learning. Strong Python skills and hands-on experience with ML libraries (e.g., scikit-learn, XGBoost, PyTorch, TensorFlow). Proficient with Databricks, MLflow, and PySpark. Solid understanding of model lifecycle and MLOps practices. Experience with AWS-based data ...

Skills: 5+ years of experience in ML Engineering or Applied Machine Learning. Strong Python skills and hands-on experience with ML libraries (e.g., scikit-learn, XGBoost, PyTorch, TensorFlow). Proficient with Databricks, MLflow, and PySpark. Solid understanding of model lifecycle and MLOps practices. Experience with AWS-based data ...