1 to 25 of 27 Remote/Hybrid scikit-learn Jobs

bids, proofs of concept and customer workshops. QualificationsRequired SkillsStrong Python development skills with experience using AI/ML frameworks such as PyTorch, TensorFlow, Scikit-Learn and Hugging Face. Proven experience developing and deploying machine learning solutions, including deep learning, computer vision, NLP/LLMs or time-series analytics. ...

anomalies. Answer questions like: "What happened?" "Why did performance drop last quarter?" Programming & Tools: Work with: Python, R, SQL, Machine learning frameworks (TensorFlow, Scikit-learn), Use big data technologies (Spark, Hadoop) when needed Data Visualization & Communication: Present complex findings in understandable formats, Build visualizations or dashboards to communicate ...

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 ...

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 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 ...

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/ ...

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/ ...

youYou 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 TensorFlowStrong experience with AWS ML services (SageMaker, Lambda, S3) in production environmentsStrong experiment design skills: hypothesis formulation, A/ ...

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/ ...

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

intelligent automation solutions. AI/ML Engineering: Practical experience building and deploying AI/ML models using frameworks such as Python, TensorFlow, PyTorch, scikit-learn, or Azure AI services. Software Engineering: Strong programming skills in Python, C#, .NET, PowerShell, or similar languages, with experience building REST APIs, microservices ...

science processes. Experience in translating customer requirements into technical requirements and development objectives. Python expertise covering standard data science libraries (NumPy, pandas, matplotlib, Scikit-learn, PyTorch, etc ), web frameworks (Flask or FastAPI) and visualisation (Dash, Plotly, & Streamlit). Proficient in SQL. Working with unstructured data Building customer ...

science processes. Experience in translating customer requirements into technical requirements and development objectives. Python expertise covering standard data science libraries (NumPy, pandas, matplotlib, Scikit-learn, PyTorch, etc...), web frameworks (Flask or FastAPI) and visualisation (Dash, Plotly, & Streamlit). Proficient in SQL. Working with unstructured data Building customer ...

science processes. · Experience in translating customer requirements into technical requirements and development objectives. · Python expertise covering standard data science libraries (NumPy, pandas, matplotlib, Scikit-learn, PyTorch, etc...), web frameworks (Flask or FastAPI) and visualisation (Dash, Plotly, & Streamlit). · Proficient in SQL. · Working with unstructured data · Building customer ...

deployment. Key Skills Strong Python and SQL skills. Experience building and deploying ML models in production. Hands-on knowledge of machine learning frameworks (Scikit-learn, TensorFlow, PyTorch). Data engineering and pipeline development experience. Cloud experience (AWS, Azure, or GCP). Strong understanding of software engineering best practices. ...

design, integration, data, CI/CD, observability, security, and cloud‐native practices. Strong Python skills and experience with frameworks such as PyTorch, TensorFlow, scikit-learn, LangChain, LangGraph, or similar. Experience with LLM and agentic patterns, including retrieval, orchestration, tool use, evaluation, guardrails, and governed production deployment. Solid understanding ...

used, why you chose them and what alternatives you considered. Python: Strong proficiency in Python and its data/ML ecosystem (pandas, NumPy, scikit-learn), writing maintainable, production-quality code. AWS: Hands-on experience building, training and deploying ML models on the AWS stack, ideally with experience ...

used, why you chose them and what alternatives you considered. Python: Strong proficiency in Python and its data/ML ecosystem (pandas, NumPy, scikit-learn), writing maintainable, production-quality code. AWS: Hands-on experience building, training and deploying ML models on the AWS stack, ideally with experience ...

causal inference Experience designing and evaluating marketing experiments and lift studies Advanced SQL skills and hands-on Python experience, ideally including pandas, scikit-learn, statsmodels, or similar libraries Familiarity with modern data platforms such as Snowflake, dbt, and cloud-based analytics environments Understanding of digital advertising platforms, attribution ...

/LangChain/LangGraph/AI Agents/Enterprise Search/Neural Networks/Model Deployment/Edge AI/TensorFlow/scikit-learn/Linux/Git/Machine Learning/Artificial Intelligence/Computer Science/Mathematics/Statistics RedTech Recruitment Ltd focus on finding roles ...

Marketing experimentation Strong statistical background covering: Hypothesis testing Causal inference Power analysis Sample size calculation Regression modelling Strong SQL skills. Python experience (pandas, scikit-learn, scipy, statsmodels). Experience working with modern analytics stacks. Ability to communicate technical concepts to marketing and commercial stakeholders. Comfortable using ...

successful implementation. Machine Learning Engineer, key skills: Experience: Proven background as a Machine Learning Engineer Programming skills: Strong in SQL and Python (Pandas, Scikit-learn, Jupyter, Matplotlib) Data transformation & manipulation : experience with Airflow, DBT and Kubeflow Cloud: Experience with GCP and Vertex AI (developing ML services) Expertise: Solid ...

production and kept working. Statistics and experimentation: hypothesis testing, A/B testing, power and sample sizing. Classical ML: classification and ranking with scikit-learn and XGBoost or LightGBM, evaluated rigorously: validation design, calibration, leakage. Decision science: applied work with at least one of contextual bandits, causal inference ...

Proven success in leading the design, development, and deployment of sophisticated predictive models. Expertise in Python/R and ML frameworks, such as scikit-learn, TensorFlow, or PyTorch, Proven ability to design and implement complex machine learning solutions and guiding best practice. Deep understanding of statistical analysis ...

training and evaluation of tabular models, using neural networks or gradient-boosted trees. Experience with PyTorch, PyTorch Lightning, TensorFlow, XGBoost, CatBoost or scikit-learn could all be relevant; no single framework is required. Experience designing features and labels, choosing metrics for the decision a model makes and judging ...