1 to 25 of 32 Remote/Hybrid scikit-learn Jobs

years) as a Machine Learning Engineer , Data Scientist , or similar role. Strong programming skills in Python (experience with libraries such as TensorFlow, PyTorch, scikit-learn, pandas, NumPy). Solid understanding of machine learning algorithms , statistical modelling , and deep learning architectures . Hands-on experience with MLOps tools ...

Skills AI/Technical Strong experience building and deploying machine learning and AI solutions in production. Hands‐on experience with: Python (PyTorch, TensorFlow, scikit‐learn) Data engineering tools (SQL, Spark, Airflow or similar) LLMs, NLP, and document intelligence (e.g. RAG, embeddings) Experience with cloud platforms (AWS, 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 ...

/CD pipelines and manage model deployment using Kubernetes/OpenShift and MLOps principles. Technical Requirements Core Programming: Expert-level Python (Pandas, NumPy, scikit-learn, PyTorch/TensorFlow, FastAPI, LangChain, LlamaIndex). Generative AI: Deep experience with LLMs (Gemini, OpenAI, Claude, Llama) and evaluating model safety/performance ...

between data and lived football judgement Essential Requirements Technical Skills Advanced proficiency in Python and the data science stack (pandas/polars, scikit-learn, NumPy, matplotlib/plotly) Strong SQL skills ability to design schemas, write complex queries, and manage relational data across large datasets Demonstrated experience integrating ...

date with the latest advancements in machine learning and AI technologies Required Skills & Experience Strong programming skills in Python (e.g., TensorFlow, PyTorch, Scikit-learn) Experience deploying ML models using cloud platforms (AWS, Azure, or GCP) Solid understanding of machine learning algorithms, data structures, and software engineering principles Experience ...

Russell Group university in Data Science, Computer Science, Mathematics, Physics, Engineering, or a related discipline Strong programming skills in Python (e.g. NumPy, pandas, scikit-learn, matplotlib); R is also welcome A solid understanding of core machine learning concepts, data wrangling, and model evaluation Proficiency with SQL and experience ...

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. ...

Tableau or Power BI. Published work, patents or conference presentations related to AI or data science in finance. Technical Skills Programming: Python (pandas, scikit‐learn, TensorFlow/PyTorch), R, SQL, Jupyter notebooks and version control (Git). Machine Learning: regression, classification, clustering, tree‐based models, neural networks, MLOps ...

talented ML Ops Engineer to join our growing teams. Key Responsibilities Strong proficiency in Python and ML libraries such as: pandas, NumPy, scikit-learn XGBoost, LightGBM, CatBoost TensorFlow, Keras, PyTorch Experience with model deployment and serving tools: ONNX, TensorRT, TensorFlow Serving, TorchServe Familiarity with ML lifecycle tools: MLflow ...

databases, visualization tools). Published research, patents, or conference presentations in AI or data science related to finance. Technical Skills Programming: Python (pandas, scikit‐learn, TensorFlow/PyTorch), R, SQL, notebooks, Git. Machine Learning: regression, classification, clustering, tree‐based models, neural networks; MLOps, model deployment, automated testing. Data ...

Currently pursuing or recently completed a degree in Data Science, Computer Science, Statistics, Mathematics , or related field Strong foundation in Python (Pandas, NumPy, Scikit-learn) Understanding of machine learning concepts (regression, classification, clustering) Experience with data visualization tools (Matplotlib, Seaborn, or similar) Familiarity with SQL and working with ...

classical CV algorithms (edge detection, thresholding, color spaces). Data Analytics Fluency: Experience working with standard data manipulation libraries (NumPy, pandas, scikit-learn, SciPy). Communication: Advanced English proficiency to collaborate effectively in a global environment. Bonus Points (Nice to Have) Hands-on experience with Vision Transformers (ViTs ...

understanding of two-tower neural networks, embedding techniques, and ranking models. Proficiency in Python with familiarity to ML libraries e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku. Experience with ML Ops, including model deployment, monitoring, and retraining ...

SparkSQL in data or ML-focused roles. Strong understanding of machine learning concepts and experience using common ML libraries such as scikit‐learn, TensorFlow or PyTorch, alongside packages such as NumPy and Pandas. Knowledge of natural language processing techniques and API integration patterns for ML services. Experience delivering ...

Scientist with production ML exposure Strong understanding of ML algorithms, model development, and deployment Experience with Python and ML frameworks (e.g. TensorFlow, PyTorch, scikit-learn) Familiarity with data pipelines and cloud or on-prem environments Understanding of MLOps principles Ability to work in secure or regulated environments Eligibility ...

products Deep GenAI and classical ML expertise Hands-on experience with Agentic AI, evaluation frameworks, RAG and prompt engineering Strong Python skills (PyTorch, scikit-learn, modern ML frameworks) A commercial mindset, balancing tech investment with customer value The credibility to lead technically and influence at exec level Desirable ...

independently and take ownership of complex problems Strong communication skills, with the ability to explain technical concepts clearly Technical Environment Python (e.g. pandas, scikit-learn, TensorFlow/PyTorch where relevant) SQL and large-scale data processing Cloud-based environments (e.g. AWS, Azure, or similar) Experience with model deployment ...

measurable impact Experience taking models into production and managing performance over time Prior experience leading or mentoring Data Scientists Strong Python (pandas, numpy, scikit-learn or similar) Strong SQL (complex joins, aggregations, analytical functions) Solid grounding in applied statistics, evaluation design, calibration, bias/fairness Experience working closely ...

including, University degree (STEM or quantitative discipline) Strong foundations in mathematics and analytical reasoning Strong hands-on experience with, programming & Analytics: Python, SQL, Scikit-learn, TensorFlow Data & Cloud: AWS (Athena, S3, Redshift), data warehousing, ETL pipelines Visualisation & Tools: Jupyter, Visual Studio Code, Microsoft Excel, dashboards and reporting solutions ...

including, University degree (STEM or quantitative discipline) Strong foundations in mathematics and analytical reasoning Strong hands-on experience with, programming & Analytics: Python, SQL, Scikit-learn, TensorFlow Data & Cloud: AWS (Athena, S3, Redshift), data warehousing, ETL pipelines Visualisation & Tools: Jupyter, Visual Studio Code, Microsoft Excel, dashboards and reporting solutions ...

work on Production-grade ML pipelines Model governance & lifecycle management Feature engineering at scale Embedding ML into agent-based systems Core stack Python · scikit-learn · MLflow · SQL · Docker · Feature Stores Nice to have Explainable AI · Anomaly Detection · LLM/NLP integration · Real-time inference ...

environments. We're looking for individuals with: Experience: Proven background as a Machine Learning Engineer. Technical 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). ...

environments. We're looking for individuals with: Experience: Proven background as a Machine Learning Engineer. Technical 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). ...

real-world problems. Mastery of Python/R, with extensive experience in designing and implementing complex machine learning solutions using frameworks such as scikit-learn, TensorFlow, or PyTorch. Excellent verbal and written communication skills for presenting complex data-driven insights to both technical and non-technical audiences. Strong ...