1 to 25 of 126 scikit-learn Jobs

Skills/Knowledge/Experience Data Science & ML Supervised and unsupervised learning Time series, NLP, recommendation systems (as applicable) Programming Python (NumPy, Pandas, Scikit learn) Optional: R, SQL Data Platforms Relational & NoSQL databases Big data frameworks (Spark, Hive, Databricks) MLOps & Deployment Model lifecycle management CI/CD pipelines ...

Python, R, or SQL, and experience with various data science and machine learning libraries. Experience with libraries/frameworks like NumPy, Pandas, SciPy, Scikit‐learn, TensorFlow, PyTorch, Transformers, Langchain, Streamlit, or Gradio, among others. Experience with cloud‐based tools for production use (e.g., AWS SageMaker, AWS Bedrock, Vertex ...

mentorship to junior engineers Required Experience & Skills Core Technical Skills Strong hands‐on experience with Python , and at least one of: TensorFlow, PyTorch, scikit‐learn Practical experience with LLMs and Generative AI , including: Prompt engineering Retrieval‐Augmented Generation (RAG) Agentic workflows Experience deploying AI on cloud platforms (Azure ...

practices for data governance, security, and MLOps on GCP Proficiency with Python and common AI/ML frameworks such as TensorFlow, PyTorch, JAX, scikit learn, and Hugging Face libraries Knowledge of MLOps and LLMOps practices-including CI/CD for models, model registry/versioning, feature stores, orchestration ...

practices for data governance, security, and MLOps on GCP. Proficiency with Python and common AI/ML frameworks such as TensorFlow, PyTorch, JAX, scikit learn, and Hugging Face libraries. Knowledge of MLOps and LLMOps practicesincluding CI/CD for models, model registry/versioning, feature stores, orchestration ...

Hands-on experience with LLM frameworks and tools like LangChain , LlamaIndex etc Expertise in Python and its data science ecosystem (e.g., Pandas, NumPy, Scikit-learn). Proven experience with one or more deep learning frameworks, such as TensorFlow or PyTorch. Hands-on experience with a major cloud platform ...

stack products Strong backend (Node.js, Python/Flask, FastAPI) and frontend (React, Next.js, Vue) fundamentals ML/data science proficiency: Python, SQL, pandas, scikit-learn, PyTorch/TensorFlow Experience with cloud platforms (AWS, GCP, Azure) and containerisation (Docker, Kubernetes) Proven ability to build data-secure, privacy-compliant infrastructure ...

complex, real-world problems through data science and analytics. Experience coaching and reviewing work of junior team members. Strong Python skills (pandas, numpy, scikit-learn) and a solid grounding in probability and statistics. Deep knowledge of machine learning methods and their practical application. Experience managing multiple ...

modelling, experimental design, and evaluation metrics (e.g. precision, recall, AUC, RMSE) ● Strong Python skills, with experience using libraries such as TensorFlow, PyTorch, and scikit-learn ● Expertise in relational databases (particularly PostgreSQL), including schema design and query optimisation ● Experience with modern engineering practices (CI/CD, Docker, Kubernetes) ● Strong ...

engaging with non-technical stakeholders to scope, design and build an appropriate ML solution. Proficient with Python data science stack, e.g., pandas, scikit-learn, Jupyter etc., and version control, e.g., Git. Exposure to LLMOps, model monitoring principles, CI/CD and associated tech, e.g., Docker, MLflow, k8s, FastAPI ...

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. ...

Experience Minimum 1+ year of commercial experience in machine learning or data science Strong Python skills with experience in ML frameworks such as scikit-learn, PyTorch, TensorFlow, or XGBoost Exposure to AWS services (e.g. S3, Lambda, SageMaker) Understanding of core ML concepts: model evaluation, validation, and experimentation Familiarity ...

will have experience in many of the following: Hands-on experience developing and deploying ML models in Python using frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow Strong experience with AWS ML services (SageMaker, Lambda, S3) in production environments Strong experiment design skills: hypothesis formulation, A/ ...

ensure seamless data availability for decision‐making. Your Skills Strong expertise in Python and Scala, with hands‐on experience in Pandas, NumPy, Scikit‐learn, PySpark, and MLlib. Solid SQL skills and experience working with large‐scale, big‐data frameworks (e.g., Spark, Hadoop). Familiarity with major cloud platforms ...

lifecycle, from feature engineering to deployment and monitoring Build and maintain data pipelines and production workflows using Python, TensorFlow, PyTorch, scikit-learn, AWS (S3, Lambda, SageMaker, Step Functions, Bedrock), Snowflake, and Dataiku Apply MLOps best practices, including CI/CD, automated testing, model versioning, and observability Define deployment ...

university is a great indicator, though it's your depth of applied expertise that matters most. Technically, you bring: Python fluency (NumPy, Pandas, Scikit-Learn, PyTorch) and solid TypeScript/API skills Hands-on experience with LLMs prompt engineering, evaluation, RAG architectures, safety considerations Cloud-native development ...

experience as a Machine Learning Engineer or equivalent role Hands-on experience developing and deploying ML models in Python using frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow Strong experience with cloud-based ML deployment (e.g., AWS SageMaker, Lambda, S3) Knowledge of MLOps/LLMOps tooling (e.g. ...

Python (or similar experience with a desire to develop Python skills) Familiarity with essential data science tools and libraries (e.g. NumPy, Pandas, Scikit-Learn) and machine learning (e.g. PyTorch, Tensorflow, Huggingface, LangChain, LiteLLM). A high level of competence in applied maths, statistics and scientific methods. Clear written ...

Python (or similar experience with a desire to develop Python skills) Familiarity with essential data science tools and libraries (e.g. NumPy, Pandas, Scikit-Learn) and machine learning (e.g. PyTorch, Tensorflow, Huggingface, LangChain, LiteLLM). A high level of competence in applied maths, statistics and scientific methods. Clear written ...

Python (or similar experience with a desire to develop Python skills) Familiarity with essential data science tools and libraries (e.g. NumPy, Pandas, Scikit-Learn) and machine learning (e.g. PyTorch, Tensorflow, Huggingface, LangChain, LiteLLM). A high level of competence in applied maths, statistics and scientific methods. Clear written ...

Python (or similar experience with a desire to develop Python skills) Familiarity with essential data science tools and libraries (e.g. NumPy, Pandas, Scikit-Learn) and machine learning (e.g. PyTorch, Tensorflow, Huggingface, LangChain, LiteLLM). A high level of competence in applied maths, statistics and scientific methods. Clear written ...

data science expertise Machine learning and AI delivery Generative AI/LLM experience Strong Python skills and familiarity with core libraries (pandas, NumPy, scikit‐learn) Deep learning and NLP stacks (PyTorch, HuggingFace Transformers) MLOps and model operationalization Responsible AI awareness Additional Requirements: Security clearance (SC/BPSS ...

delivering ML/AI solutions into production environments Strong Python expertise and experience with modern AI/ML frameworks such as: PyTorch TensorFlow scikit-learn NumPy Pandas Hands-on experience with Generative AI, agentic AI systems, and AI testing frameworks Strong communication skills and a passion for clear ...

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 ...

ability to build trusted relationships across technical and non-technical teams at all levels. Advanced Python skills with strong data science fundamentals (pandas, scikit-learn, XGBoost, statsmodels, or similar). A rigorous, evidence-driven approach to model development with strong problem-solving ability. A commercial mindset - you instinctively ...