1 to 25 of 120 scikit-learn Jobs

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 ...

agents). Strong proficiency in Python for AI/ML development, including use of common ML and data libraries (e.g. TensorFlow/PyTorch, scikit-learn, pandas, NumPy). Proven experience integrating AI services with enterprise systems via APIs and event-driven architectures. Practical experience with LLMs, prompt engineering ...

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 ...

writing clean, efficient, and maintainable code to enable scalable and production-grade AI/ML solutions. Extensive experience with machine learning frameworks (e.g., Scikit-learn, TensorFlow, PyTorch), with the ability to design, implement, and optimise scalable solutions while guiding teams in the effective use of these tools. Extensive ...

following: Commercial experience developing AI or Machine Learning solutions Strong Python development skills Experience with Machine Learning frameworks such as TensorFlow, PyTorch or Scikit-learn Experience with Generative AI technologies including LLMs, LangChain or LlamaIndex Hands-on experience building RAG solutions and working with vector databases Experience with ...

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 ...

maintainable code for developing and deploying reliable AI/ML solutions in production environments. Hands-on experience using machine learning frameworks (e.g., Scikit-learn, TensorFlow, PyTorch) to design and implement solutions. Experience deploying AI/ML models to production systems in collaboration with engineering teams. Experience working with ...

writing clean, efficient code for AI/ML solutions. Hands-on experience, through study, internships, or personal projects, with machine learning frameworks (e.g., Scikit-learn, TensorFlow, PyTorch). Exposure to supporting the deployment of AI/ML models, working alongside engineering colleagues. Some exposure to generative AI concepts ...

Machine Learning Engineer Strong experience developing and deploying Machine Learning models using Python Experience with frameworks such as PyTorch, TensorFlow, Scikit-learn or XGBoost Knowledge of AWS cloud services including SageMaker, Lambda and S3 Experience with MLOps tools such as MLflow, Weights & Biases or Data Version Control Experience ...

tooling (e.g. MLflow, Weights & Biases, DVC, Airflow) Strong experience with Python and associated scientific software packages such as PyTorch, OpenCV, Pandas, SciPy, NumPy, SciKit-learn, etc. Strong software engineering practices including version control, code review, software testing methodologies, and continuous integration; experience with IEC 62304 is particularly desirable ...

applications in large scale production environments. Experience managing data science teams and couching team members Proficiency in Python and ML frameworks (PyTorch, TensorFlow, scikit-learn). Hands-on experience with agentic frameworks (LangChain, CrewAI, AutoGen, LangGraph, ADK). Experience with generative models (transformers, GANs/VAEs; diffusion models ...

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 ...

experience across data science and machine learning workflows. Solid understanding of machine learning algorithms and statistical modelling. Experience using ML libraries such as scikit-learn, TensorFlow, or PyTorch. Strong knowledge of data preprocessing, feature engineering, and model evaluation. Experience working with large datasets and applying analytical techniques. Familiarity ...

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). Platform & Cloud Engineering: Architecture and delivery of scalable cloud data ...

degree in machine learning, computer science, engineering, or a related discipline, with an MScrequiredand a PhD highly desirable. Deep hands-on experience withPyTorch, Scikit-learn, and the Hugging Face ecosystem, with familiarity withMLFlowandAzureML; capable of making architecture and implementation decisions. Strong competence with Git, pull requests, automated testing ...

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 ...

Economics. Professional experience in a data science, ML engineering, or applied data role. Strong Python programming skills, including hands-on experience with pandas, scikit-learn, and at least one ML or deep learning framework. Working knowledge of Bedrock and other AWS managed services. Demonstrable experience building and deploying ...

production and supporting them post-deployment.* Strong Python programming skills, including object-oriented design and proficiency with key ML libraries (e.g., PyTorch, TensorFlow, Scikit-Learn).* Solid understanding of probability and statistical modeling to support robust model development and interpretation.* Experience with cloud platforms (especially Azure and/ ...

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 ...

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 ...

computer vision projects Knowledge of AWS, Azure, or GCP Familiarity with Docker, APIs, or Git workflowsFamiliarity with frameworks such as PyTorch, TensorFlow, or Scikit-learn Internship, university project, or personal portfolio related to AI/ML What’s on Offer Competitive graduate salary package Company stock options/ ...