76 to 100 of 250 scikit-learn Jobs

including experience with software testing (unit, integration, system), and knowledge of test-driven development; other languages are a plus. Proficiency in at least one ML framework, such as scikit-learn, XGBoost, Tensorflow, or PyTorch. Proficiency with Cloud platform(s), such as Google Cloud Platform, Amazon Web Services, or Azure. Experience in designing, and deploying ML pipelines in production More ❯

in Python, including solid experience with software testing (unit, integration, system), and knowledge of test-driven development; other languages are a plus. Proficiency in ML frameworks, such as scikit-learn, XGBoost, Tensorflow, or PyTorch. Proficiency with Cloud platform(s), such as Google Cloud Platform, Amazon Web Services, or Azure. Experience in designing, and deploying ML pipelines in production More ❯

and deploy machine learning models for real-world use cases Clean and analyze data using tools like Pandas and NumPy Build and train models with TensorFlow, PyTorch, or Scikit-learn Create scalable ML pipelines in AWS, GCP, or Azure Collaborate cross-functionally to integrate models into production Research and prototype cutting-edge AI solutions Monitor, retrain, and optimize More ❯

data pipeline orchestration and a strong grasp of DevSecOps best practices in cloud-native environments • Hands-on experience with key tools and frameworks, including: o Python, NumPy, Pandas, scikit-learn o TensorFlow or PyTorch o Elasticsearch, Logstash, Kibana • Preferred Experience in GDS (Government Digital Services) or USDS (U.S. Digital Services) Education Requirement • Shall have at a minimum, a More ❯

PhD with 4 years Deep expertise in big data platforms (e.g., Hadoop, Spark, Kafka) and multi-cloud environments (AWS, Azure, GCP) Experience with machine learning frameworks (e.g., TensorFlow, Scikit-learn, PyTorch) Strong programming skills in Python, Java, or Scala Familiarity with data pipeline development and real-time data processing Proven ability to design and implement data-intensive solutions More ❯

machine learning lifecycle Working with Data Scientists to deploy trained machine learning models into production environments Working with a range of models developed using common frameworks such as Scikit-learn, TensorFlow, or PyTorch Experience with software engineering best practices and developing applications in Python. Technical experience of cloud architecture, security, deployment, and open-source tools ideally with one More ❯

grow and shape the data science team and its role within the wider business. What We’re Looking For Strong technical foundation with proficiency in Python (Pandas, NumPy, Scikit-learn), SQL, and cloud platforms (GCP or AWS). Experience with modern data warehouses (BigQuery, Snowflake, Redshift). Proven experience in deploying machine learning models or optimisation algorithms into More ❯

grow and shape the data science team and its role within the wider business. What We’re Looking For Strong technical foundation with proficiency in Python (Pandas, NumPy, Scikit-learn), SQL, and cloud platforms (GCP or AWS). Experience with modern data warehouses (BigQuery, Snowflake, Redshift). Proven experience in deploying machine learning models or optimisation algorithms into More ❯

Experience building interactive dashboards and reporting tools. • Familiarity with data engineering, ETL processes, and data pipelines. • Experience with statistical modelling and machine learning techniques, and libraries such as scikit-learn, PyTorch, or TensorFlow. • Excellent communication skills able to explain complex analysis to non-technical stakeholders. • Proactive, inquisitive mindset with strong problem-solving skills. • Interest in cyber risk and More ❯

native or platform services using Microsoft and .NET . 4+ years in a Data Scientist or AI/ML Engineer role. Proficiency in Python , including libraries like pandas , scikit-learn , TensorFlow , and PyTorch . Deep understanding of ML algorithms : regression, classification, clustering, and deep learning. Hands-on experience with Large Language Models (LLMs) and techniques such as Retrieval More ❯

Experience building interactive dashboards and reporting tools. • Familiarity with data engineering, ETL processes, and data pipelines. • Experience with statistical modelling and machine learning techniques, and libraries such as scikit-learn, PyTorch, or TensorFlow. • Excellent communication skills—able to explain complex analysis to non-technical stakeholders. • Proactive, inquisitive mindset with strong problem-solving skills. • Interest in cyber risk and More ❯

in artificial intelligence and its application to drug discovery Understanding of ligand- and structure-based drug design. Experience with machine learning and major machine learning frameworks such as scikit-learn or PyTorch Proficiency in a low-level programming language such as C/C++ or Rust. Knowledge of advanced data analysis techniques such as multi-parameter optimization Open More ❯

large databases and data warehouses. You'll be proficient in Python, R, or other relevant programming languages and have Experience with machine learning libraries and frameworks (e.g., TensorFlow, Scikit-learn, PyTorch). With a background in data mining and pattern recognition you'll be an expert in statistical modelling, predictive analytics and regression techniques. An industry certification in More ❯

s degree with additional equivalent experience. Experience with practical application of clustering, predictive modelling, and NLP techniques, with familiarity with at least one major machine learning library (eg. Scikit-learn, statsmodels, spaCy, mlr). Proficiency in Python; knowledge of R or SQL is a plus. Familiarity with coding best practices, such as version control, functional code, and documentation More ❯

processing to sequential data and decision-making post PhD. Experience in software development for proof of concept in Python. Experience with machine and deep learning frameworks: TensorFlow, PyTorch, scikit-learn, etc. Domains of Particular Interest RF communications and CEMA Electronic or Electromagnetic Warfare (EW) Tracking and sensor data fusion Radar signal processing Acoustic data processing (including sonar) Distributed More ❯

Title: AI ML Engineer, CCaaS Location: Miramar, FL Duration: 12+ months contract to hire Compensation: $75.00 - 85.00/hr Work Requirements: US Citizen, GC Holders or Authorized to Work in the U.S. AI ML Engineer, CCaaS As an experienced engineer More ❯

evaluation frameworks. Collaborate with data scientists, software engineers, and domain experts to deliver high-impact solutions. Essential Skills Expert-level Python programming with libraries such as NumPy, Pandas, Scikit-learn, LangChain, LlamaIndex, and Azure AI Foundry. Strong experience with Azure and generative AI R&D. Practical knowledge of GenAI techniques including prompt orchestration, retrieval methods, and agentic frameworks More ❯

evaluation frameworks. Collaborate with data scientists, software engineers, and domain experts to deliver high-impact solutions. Essential Skills Expert-level Python programming with libraries such as NumPy, Pandas, Scikit-learn, LangChain, LlamaIndex, and Azure AI Foundry. Strong experience with Azure and generative AI R&D. Practical knowledge of GenAI techniques including prompt orchestration, retrieval methods, and agentic frameworks More ❯

evaluation frameworks. Collaborate with data scientists, software engineers, and domain experts to deliver high-impact solutions. Essential Skills Expert-level Python programming with libraries such as NumPy, Pandas, Scikit-learn, LangChain, LlamaIndex, and Azure AI Foundry. Strong experience with Azure and generative AI R&D. Practical knowledge of GenAI techniques including prompt orchestration, retrieval methods, and agentic frameworks More ❯

and testing Develop evaluation pipelines and ensure robust quality control across deployments Essential Skills and Experience: Advanced Python programming skills with experience in libraries such as Numpy, Pandas, Scikit-Learn, Langchain, LlamaIndex Deep expertise in Azure and its AI services, including Azure AI Foundry Hands-on experience with GenAI techniques: prompt orchestration, retrieval methods (RAG, knowledge graphs), agentic More ❯

and testing Develop evaluation pipelines and ensure robust quality control across deployments Essential Skills and Experience: Advanced Python programming skills with experience in libraries such as Numpy, Pandas, Scikit-Learn, Langchain, LlamaIndex Deep expertise in Azure and its AI services, including Azure AI Foundry Hands-on experience with GenAI techniques: prompt orchestration, retrieval methods (RAG, knowledge graphs), agentic More ❯

years experience in Generative AI experience Proven experience with language-based Generative AI eg. LangChain, LangSmith, LangGraph, RAG, Proficiency in Python, data science libraries such as numpy, Pandas, scikit-learn Experienced in LLM frameworks such as LangChain Ability to build and create prototypes in a fast-paced environment BSc/MSc in Computer Science, Physics, Mathematics, Engineering, or More ❯

years experience in Generative AI experience Proven experience with language-based Generative AI eg. LangChain, LangSmith, LangGraph, RAG, Proficiency in Python, data science libraries such as numpy, Pandas, scikit-learn Experienced in LLM frameworks such as LangChain Strong client-facing consulting or B2B experience Ability to build and create prototypes in a fast-paced environment BSc/MSc More ❯

Modelling Approaches: Machine learning, optimisation, stochastic and agent-based models About You Experience in the energy sector - markets, trading, forecasting, etc. Strong Python skills with machine learning frameworks (scikit-learn, TensorFlow, PyTorch). Knowledge of GitHub/Azure DevOps and SQL advantageous. Excellent communicator, able to explain technical concepts to non-technical audiences. Degree (or equivalent experience) in More ❯

building RAG pipelines, and experimenting with agentic AI workflows. Strong Python development skills and familiarity with modern ML and NLP frameworks and tooling (e.g. Hugging Face, spaCy, PyTorch, Scikit-learn). Familiarity with Kubernetes and infrastructure for deploying and scaling ML models is a plus. Exposure to systems integration challenges (e.g. connecting ML workflows with data stores like More ❯