1 to 25 of 440 scikit-learn Jobs

Experience Proven experience (3–5+ 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 and frameworks (e.g., MLflow, Kubeflow, SageMaker More ❯

Experience Proven experience (3–5+ 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 and frameworks (e.g., MLflow, Kubeflow, SageMaker More ❯

Experience Proven experience (3–5+ 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 and frameworks (e.g., MLflow, Kubeflow, SageMaker More ❯

Experience Proven experience (3–5+ 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 and frameworks (e.g., MLflow, Kubeflow, SageMaker More ❯

Experience Proven experience (3–5+ 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 and frameworks (e.g., MLflow, Kubeflow, SageMaker More ❯

or related field. 7+ years of professional software development experience, with at least 3 years in AI/ML. Strong proficiency in Python , including libraries like NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch . Solid understanding of ML algorithms , NLP , deep learning , and statistical methods. Experience with Docker, Kubernetes , and cloud platforms like AWS/Azure/GCP . More ❯

a financial services environment (Banking, FinTech, Insurance, or related). Technical Skills: Programming: Expert proficiency in Python (must-have) and its core data science libraries (e.g., Pandas, NumPy, Scikit-learn). Proficiency in SQL is essential. Machine Learning: Deep, hands-on experience with a wide range of ML techniques (supervised/unsupervised learning, time-series analysis, ensemble methods More ❯

in designing, implementing, and maintaining MLOps processes in a cloud environment (e.g., Azure, AWS, GCP). Technical Skills: Expertise in Python and its ML ecosystem (e.g., TensorFlow, PyTorch, Scikit-learn, Pandas, NumPy). Strong background in statistical analysis, algorithm design, and software engineering best practices. Experience with Docker and Kubernetes for containerization and orchestration. Proficiency with modern version More ❯

in designing, implementing, and maintaining MLOps processes in a cloud environment (e.g., Azure, AWS, GCP). Technical Skills: Expertise in Python and its ML ecosystem (e.g., TensorFlow, PyTorch, Scikit-learn, Pandas, NumPy). Strong background in statistical analysis, algorithm design, and software engineering best practices. Experience with Docker and Kubernetes for containerization and orchestration. Proficiency with modern version More ❯

Essential - Demonstrable experience in Machine Learning, NLP, and GenAI including LLM/SLM fine-tuning and prompt development. Proficiency in Python and data libraries such as Pandas, NumPy, Scikit-learn, PyTorch/TensorFlow. Practical knowledge in SQL/NoSQL databases and API development/integration. Proven ability to analyze model performance and optimize for accuracy, efficiency, and scalability. More ❯

analytics platforms for sensitive environments. Collaborate across engineering, security, and product teams to deliver at pace and scale. The toolkit youll use Data Science & Engineering: Python (NumPy, Pandas, scikit-learn, PyTorch/TensorFlow), SQL, NoSQL, Spark, big data ecosystems Visualisation & APIs: REST/JSON, Postman, Flask/FastAPI, Power BI/Tableau, D3.js DevOps & Cloud: CI/CD More ❯

platforms for sensitive environments. Collaborate across engineering, security, and product teams to deliver at pace and scale. The toolkit you’ll use 🌳 Data Science & Engineering: Python (NumPy, Pandas, scikit-learn, PyTorch/TensorFlow), SQL, NoSQL, Spark, big data ecosystems Visualisation & APIs: REST/JSON, Postman, Flask/FastAPI, Power BI/Tableau, D3.js DevOps & Cloud: CI/CD More ❯

platforms for sensitive environments. Collaborate across engineering, security, and product teams to deliver at pace and scale. The toolkit you’ll use 🌳 Data Science & Engineering: Python (NumPy, Pandas, scikit-learn, PyTorch/TensorFlow), SQL, NoSQL, Spark, big data ecosystems Visualisation & APIs: REST/JSON, Postman, Flask/FastAPI, Power BI/Tableau, D3.js DevOps & Cloud: CI/CD More ❯

platforms for sensitive environments. Collaborate across engineering, security, and product teams to deliver at pace and scale. The toolkit you'll use Data Science & Engineering: Python (NumPy, Pandas, scikit-learn, PyTorch/TensorFlow), SQL, NoSQL, Spark, big data ecosystems Visualisation & APIs: REST/JSON, Postman, Flask/FastAPI, Power BI/Tableau, D3.js DevOps & Cloud: CI/CD More ❯

platforms for sensitive environments. Collaborate across engineering, security, and product teams to deliver at pace and scale. The toolkit you’ll use 🌳 Data Science & Engineering: Python (NumPy, Pandas, scikit-learn, PyTorch/TensorFlow), SQL, NoSQL, Spark, big data ecosystems Visualisation & APIs: REST/JSON, Postman, Flask/FastAPI, Power BI/Tableau, D3.js DevOps & Cloud: CI/CD More ❯

platforms for sensitive environments. Collaborate across engineering, security, and product teams to deliver at pace and scale. The toolkit you’ll use 🌳 Data Science & Engineering: Python (NumPy, Pandas, scikit-learn, PyTorch/TensorFlow), SQL, NoSQL, Spark, big data ecosystems Visualisation & APIs: REST/JSON, Postman, Flask/FastAPI, Power BI/Tableau, D3.js DevOps & Cloud: CI/CD More ❯

platforms for sensitive environments. Collaborate across engineering, security, and product teams to deliver at pace and scale. The toolkit you’ll use 🌳 Data Science & Engineering: Python (NumPy, Pandas, scikit-learn, PyTorch/TensorFlow), SQL, NoSQL, Spark, big data ecosystems Visualisation & APIs: REST/JSON, Postman, Flask/FastAPI, Power BI/Tableau, D3.js DevOps & Cloud: CI/CD More ❯

and machine learning/AI engineering roles (building, deploying, operating machine learning models and AI systemsExpertise in programming languages such as Python, and framework experience (e.g., TensorFlow, PyTorch, scikit-learn, KerasProven track record in designing, building, deploying production-grade ML/AI systems in real-world settings.Deep experience in feature engineering, model development, tuning, validation, and model evaluation More ❯

AI, with a strong portfolio of high-impact projects in production Expert-level programming skills in Python and SQL, and fluency with leading ML/AI frameworks (e.g., scikit-learn, TensorFlow, PyTorch) Direct experience with GenAI/LLM technologies, including tools like Hugging Face, LangChain, OpenAI APIs, vector databases, and fine-tuning methods Deep knowledge of machine learning More ❯

ML, data science, or applied statistics Solid programming skills in Python (or similar languages) Familiarity with data science or AI libraries such as Pandas, NumPy, TensorFlow, PyTorch, or Scikit-learn Strong problem-solving ability and analytical thinking A willingness to learn and work collaboratively in a team environment Nice to Have (But Not Required): Experience from a More ❯

ML, data science, or applied statistics Solid programming skills in Python (or similar languages) Familiarity with data science or AI libraries such as Pandas, NumPy, TensorFlow, PyTorch, or Scikit-learn Strong problem-solving ability and analytical thinking A willingness to learn and work collaboratively in a team environment Nice to Have (But Not Required): Experience from a More ❯

ML, data science, or applied statistics Solid programming skills in Python (or similar languages) Familiarity with data science or AI libraries such as Pandas, NumPy, TensorFlow, PyTorch, or Scikit-learn Strong problem-solving ability and analytical thinking A willingness to learn and work collaboratively in a team environment Nice to Have (But Not Required): Experience from a More ❯

ML, data science, or applied statistics Solid programming skills in Python (or similar languages) Familiarity with data science or AI libraries such as Pandas, NumPy, TensorFlow, PyTorch, or Scikit-learn Strong problem-solving ability and analytical thinking A willingness to learn and work collaboratively in a team environment Nice to Have (But Not Required): Experience from a More ❯

and data science. Mandatory Skills Description: Minimum 8+ years of hands-on experience in Data Science with strong expertise in Python and libraries such as Pandas, NumPy, SciPy, Scikit-learn, TensorFlow, or PyTorch. Proven ability to design, develop, and deploy machine learning, deep learning, and predictive models to solve complex business problems. Strong background in statistical analysis, data More ❯

and data science. Mandatory Skills Description: Minimum 8+ years of hands-on experience in Data Science with strong expertise in Python and libraries such as Pandas, NumPy, SciPy, Scikit-learn, TensorFlow, or PyTorch. Proven ability to design, develop, and deploy machine learning, deep learning, and predictive models to solve complex business problems. Strong background in statistical analysis, data More ❯