26 to 50 of 143 Permanent scikit-learn Jobs

with modern deep learning frameworks (e.g. PyTorch, TensorFlow), fine-tuning or distillation of LLMs (e.g., GPT, Llama, Claude, Gemini), machine learning libraries (e.g. scikit-learn, XGBoost). Experience with data storage for AI, vector databases, semantic search, and knowledge graphs. Contributions to open-source AI projects or research ...

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/ ...

research in machine learning, computational chemistry, and bioinformatics. Required Skills & Experience Proficiency in Python and the core data science ecosystem (e.g., Pandas, NumPy, Scikit-learn). Hands on experience with a modern deep learning framework, preferably PyTorch. Strong theoretical understanding of machine learning principles, including deep learning ...

systems, personalisation, or deep learning is desirable but not essential. Solid Python skills and experience with ML libraries such as pandas, numpy, scipy, scikit-learn, TensorFlow or PyTorch. Experience working across cloud environments (GCP, AWS, or Azure) and analytics platforms such as Dataiku. Good understanding of MLOps practices ...

Statistics, or related field Strong programming skills in Python (and optionally R, Java, or C++) Knowledge of ML frameworks like TensorFlow, PyTorch, or scikit-learn Eagerness to learn, curiosity, and a problem-solving mindset Nice to Have Cloud experience (AWS, GCP, Azure) Familiarity with MLOps tools (Docker ...

uphold best practices for deploying ML at scale Key skills & experience: • Strong Python and software engineering fundamentals • Experience operationalising ML models (e.g. Scikit-learn, TensorFlow, PyTorch) • Hands-on cloud experience (AWS, Azure or GCP), including security considerations • Containerisation and orchestration (Docker, Kubernetes) • Solid grounding in core ML concepts ...

solutions Implement experiment tracking and monitoring Collaborate with data scientists and engineers What We're Looking For: Proficiency in Python and ML frameworks (scikit-learn, PyTorch, TensorFlow) Hands-on experience with AWS ML services (SageMaker, Lambda) Familiarity with containerisation (Docker) and orchestration (Kubernetes/ECS) Knowledge of LLMOps ...

junior data scientists and help shape AI best practice Requirements Strong experience in AI, machine learning and statistics Python expertise (e.g. pandas, NumPy, scikit-learn, PyTorch, transformers) Experience deploying models and working with cloud platforms (AWS preferred) Ability to communicate complex technical concepts clearly Desirable AWS services (SageMaker ...

looking for Strong experience with Python and SQL (model building, analysis, visualisation) Solid understanding of data science techniques and libraries (Pandas, scikit-learn, supervised & unsupervised models, tree-based models) Proven experience with customer analytics (e.g. churn, CLTV, segmentation) - required Hands-on experience deploying ML models into production Exposure ...

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/ ...

experience delivering Data Science or Machine Learning solutions in a commercial setting. Strong programming skills in Python (preferred) or R, with experience using scikit-learn, pandas, PySpark or similar. Solid SQL skills and experience working with cloud environments (Azure advantageous). Hands-on experience with Databricks, model deployment ...

practices What we’re looking for: Proven client-facing experience with strong stakeholder management Proficiency across Python or Java, ML frameworks (TensorFlow, PyTorch, scikit-learn), and cloud AI services Knowledge of agentic tools such as LangChain Agents, AutoGPT, and CrewAI, plus familiarity with GenAI/LLM integrations (e.g. ...

years' experience in ML/AI engineering or data science roles (senior level). Hands-on experience with Python ML frameworks (scikit-learn, PyTorch, TensorFlow, XGBoost). Experience with AWS ML services (SageMaker, Lambda, S3) and MLOps/LLMOps tooling (MLflow, Weights & Biases, DVC). Proven track record ...

with support from more experienced colleagues. Some experience presenting technical findings to non-technical stakeholders. Proficient with the Python data science stack (pandas, scikit-learn, Jupyter, etc.) and version control tools like Git. Any exposure to LLMOps, model monitoring, CI/CD and related technologies (Docker, MLflow, Kubernetes ...

engineers to productionise models Communicate insights to technical and non-technical stakeholders Mentor junior team members Skillset: Strong Python and ML libraries (scikit-learn, PyTorch, pandas, NumPy) Experience with AWS cloud services (SageMaker, Lambda, S3) Familiarity with MLOps tools (MLflow, Weights & Biases) Knowledge of NLP, computer vision ...

stakeholders Mentor junior engineers and contribute to team best practices This role is for you if you have: Strong Python ML experience (e.g. scikit-learn, XGBoost, PyTorch, or TensorFlow) Production experience with AWS ML services (e.g. SageMaker, Lambda, S3) Proven ability to move models from experimentation into live ...

SageMaker, Lambda, Redshift). Proven ability to design and implement machine learning algorithms and models. Proficiency in Python, SQL, and ML libraries (e.g., scikit-learn, XGBoost, PyTorch, TensorFlow). Strong data analysis, statistical modelling, and experimentation skills. Experience with data visualisation tools and techniques. Proficiency in programming languages ...

preferred; AWS/Azure acceptable) Experience with GenAI/LLMs (commercial or serious hands-on experimentation) Strong Python and modern ML tooling (e.g. scikit-learn, XGBoost, TensorFlow or PyTorch) Clear interest in crypto/blockchain (commercial experience a plus, curiosity required) Responsibilities Build, train, and improve ML models ...

data analysis or data science (graduate roles, internships, placements, or academic projects welcome) 🐍 Strong Python experience for data analysis and modelling (pandas, NumPy, scikit-learn or similar) 🗄 Solid experience working with SQL and structured datasets ☁️ Hands-on experience using AWS (e.g. S3, RDS, Athena, Glue, or similar ...

Data Science or Data Engineering. Experience with NLP for entity and relationship extraction is a plus. Strongly skilled in standard ML workflows (Scikit-Learn, XGBoost) Experience with geospatial data (GIS, GeoPandas) is valued. Education MSc in Computer Science, Data Science, or a related engineering field (PhD welcome ...

Fundamentals: You aren't limited to APIs. You have a background in training and evaluating models (TensorFlow/PyTorch/Keras/Scikit-learn) and know when a simple classifier is better than a generative model. Data Fluency: You understand how to build datasets from scratch (bootstrapping, crowdsourcing ...

conversational AI, recommendation systems, optimisation, or marketing analytics. Deep understanding of ML fundamentals across the full lifecycle. Hands‐on experience with ML frameworks (scikit‐learn, XGBoost, PyTorch, TensorFlow, LightGBM). Strong exposure to LLMs, prompt engineering, RAG, and evaluation frameworks. Familiarity with MLOps tooling: CI/CD, experiment ...

engineers to forecast key company KPIs, design real-time dashboards, and develop best-in-class data infrastructure. Key Requirements Strong Python (pandas, NumPy, scikit-learn; PyTorch/TensorFlow a plus) and SQL skills Experience applying advanced analytics or ML to real-world data (finance, fintech, or forecasting contexts ...

related discipline Strong Python skills and a solid understanding of core machine learning concepts Familiarity with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn Strong analytical and problem-solving skills A genuine interest in AI and emerging technologies Nice to Have Exposure to NLP, computer vision ...

multiple domains (NLP, vision, audio, time series, tabular data). Proficient in Python and relevant ML/data science libraries (e.g., pandas, numpy, scikit-learn, PyTorch, transformers). Experience with cloud-based model deployment (AWS) and ML engineering best practices. Excellent communication, problem-solving, and project delivery skills. ...