1 to 25 of 393 Remote Algorithms Jobs

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, Vertex AI). Experience with data engineering concepts — ETL pipelines, data More ❯

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, Vertex AI). Experience with data engineering concepts — ETL pipelines, data More ❯

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, Vertex AI). Experience with data engineering concepts — ETL pipelines, data More ❯

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, Vertex AI). Experience with data engineering concepts — ETL pipelines, data More ❯

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, Vertex AI). Experience with data engineering concepts — ETL pipelines, data More ❯

building streaming data processing and ingestion pipelines Experience building distributed data processing systems which handle a high volume of client queries Strong knowledge of object oriented programming, data structures, algorithms and design patterns Prior experience building systems used by multiple technical and non-technical teams Over 6 years' experience in Financial industry About Goldman Sachs At Goldman Sachs, we commit More ❯

Computer Science, Data Science, Artificial Intelligence, Mathematics, or a related field 🐍 Proficiency in Python and familiarity with libraries such as TensorFlow, PyTorch, or scikit-learn 🧩 Understanding of machine learning algorithms and statistical modelling 📈 Strong problem-solving and analytical mindset 🗣 Excellent communication skills and a genuine passion for learning Nice to Have: 💾 Experience with SQL, data pipelines , or cloud platforms ( AWS More ❯

Computer Science, Data Science, Artificial Intelligence, Mathematics, or a related field 🐍 Proficiency in Python and familiarity with libraries such as TensorFlow, PyTorch, or scikit-learn 🧩 Understanding of machine learning algorithms and statistical modelling 📈 Strong problem-solving and analytical mindset 🗣 Excellent communication skills and a genuine passion for learning Nice to Have: 💾 Experience with SQL, data pipelines , or cloud platforms ( AWS More ❯

Computer Science, Data Science, Artificial Intelligence, Mathematics, or a related field 🐍 Proficiency in Python and familiarity with libraries such as TensorFlow, PyTorch, or scikit-learn 🧩 Understanding of machine learning algorithms and statistical modelling 📈 Strong problem-solving and analytical mindset 🗣 Excellent communication skills and a genuine passion for learning Nice to Have: 💾 Experience with SQL, data pipelines , or cloud platforms ( AWS More ❯

Computer Science, Data Science, Artificial Intelligence, Mathematics, or a related field 🐍 Proficiency in Python and familiarity with libraries such as TensorFlow, PyTorch, or scikit-learn 🧩 Understanding of machine learning algorithms and statistical modelling 📈 Strong problem-solving and analytical mindset 🗣 Excellent communication skills and a genuine passion for learning Nice to Have: 💾 Experience with SQL, data pipelines , or cloud platforms ( AWS More ❯

Computer Science, Data Science, Artificial Intelligence, Mathematics, or a related field 🐍 Proficiency in Python and familiarity with libraries such as TensorFlow, PyTorch, or scikit-learn 🧩 Understanding of machine learning algorithms and statistical modelling 📈 Strong problem-solving and analytical mindset 🗣 Excellent communication skills and a genuine passion for learning Nice to Have: 💾 Experience with SQL, data pipelines , or cloud platforms ( AWS More ❯

React, CSS, Node, Angular, etc.) Proficiency in at least one general-purpose programming language (Python preferred; Java, C++, etc. also considered) Understanding of core computer science principles (data structures, algorithms, complexity) Exposure to DevOps practices (e.g., GitHub workflows, CI/CD) Desirable: experience with Azure or healthcare-related data projects Bonus: interest in machine learning, data engineering, or visualization What More ❯

drive continuous improvement.Desirable Extensive experience of developing complex modelling applications in an underwriting environment Working knowledge and experience of Python - developing applications for pricing and modelling to implement pricing algorithms; Cloud development + Familiarity with Docker and Kubernetes. + Proficiency in AWS or Azure; Knowledge of design patterns and able to implement where appropriate; Working knowledge of software delivery and More ❯

the data utilised for analysis. • Contribute to the majority of the Data Science Project Lifecycle from idea to production • Build, validate and manage intermediate prediction, simulation, optimisation models and algorithms • Work with senior team members to define and use the key performance indicators (KPIs) and diagnostics to measure performance against business goals • Deliver training sessions for the Data Science community More ❯

the data utilised for analysis. • Contribute to the majority of the Data Science Project Lifecycle from idea to production • Build, validate and manage intermediate prediction, simulation, optimisation models and algorithms • Work with senior team members to define and use the key performance indicators (KPIs) and diagnostics to measure performance against business goals • Deliver training sessions for the Data Science community More ❯

the data utilised for analysis. • Contribute to the majority of the Data Science Project Lifecycle from idea to production • Build, validate and manage intermediate prediction, simulation, optimisation models and algorithms • Work with senior team members to define and use the key performance indicators (KPIs) and diagnostics to measure performance against business goals • Deliver training sessions for the Data Science community More ❯

the data utilised for analysis. • Contribute to the majority of the Data Science Project Lifecycle from idea to production • Build, validate and manage intermediate prediction, simulation, optimisation models and algorithms • Work with senior team members to define and use the key performance indicators (KPIs) and diagnostics to measure performance against business goals • Deliver training sessions for the Data Science community More ❯

deep learning models using tools like Python, TensorFlow, PyTorch, or Scikit-learn. Explore & Prepare Data : Help clean, transform, and analyse large datasets for AI applications. Experiment & Research : Test new algorithms, perform feature engineering, and help improve model accuracy and efficiency. Deploy & Monitor Models : Learn how to deploy models into production environments and monitor their performance over time. Collaborate Across Teams More ❯

deep learning models using tools like Python, TensorFlow, PyTorch, or Scikit-learn. Explore & Prepare Data : Help clean, transform, and analyse large datasets for AI applications. Experiment & Research : Test new algorithms, perform feature engineering, and help improve model accuracy and efficiency. Deploy & Monitor Models : Learn how to deploy models into production environments and monitor their performance over time. Collaborate Across Teams More ❯

deep learning models using tools like Python, TensorFlow, PyTorch, or Scikit-learn. Explore & Prepare Data : Help clean, transform, and analyse large datasets for AI applications. Experiment & Research : Test new algorithms, perform feature engineering, and help improve model accuracy and efficiency. Deploy & Monitor Models : Learn how to deploy models into production environments and monitor their performance over time. Collaborate Across Teams More ❯

deep learning models using tools like Python, TensorFlow, PyTorch, or Scikit-learn. Explore & Prepare Data : Help clean, transform, and analyse large datasets for AI applications. Experiment & Research : Test new algorithms, perform feature engineering, and help improve model accuracy and efficiency. Deploy & Monitor Models : Learn how to deploy models into production environments and monitor their performance over time. Collaborate Across Teams More ❯

be based in Central London As a Machine Learning Engineer for this start-up, you will have the chance to: Develop and implement cutting-edge machine learning models and algorithms that drive business outcomes and innovation. Collaborate with cross-functional teams, including data scientists, software engineers, and product managers, to deliver robust solutions. Work on diverse projects ranging from predictive More ❯

projects, fostering a culture of innovation and excellence Partner with machine learning engineers, product managers, and executives to translate data insights into tangible business and product improvements Develop scalable algorithms and automated data processing frameworks to optimize analytics workflows Technologies: AI AWS Azure Big Data Cloud ETL GCP Support Machine Learning Network PyTorch Python SQL Spark TensorFlow More: International crossfunctional More ❯

evaluation of AI/ML models for fraud detection Analyse complex datasets to identify patterns, anomalies, and insights Collaborate with developers and data scientists to validate results and refine algorithms Assist in developing blockchain use cases and understanding smart contract workflows Build dashboards, reports, or data visualisations to communicate findings to stakeholders Contribute to research into emerging technologies and their More ❯

the latest trends in AI ML and Azure technologies Required Qualifications Bachelors degree in Computer Science Data Science Engineering or related field Basic understanding of machine learning concepts and algorithms Familiarity with Python or R for data analysis and model development Exposure to Microsoft Azure services especially Azure Machine Learning and Cognitive Services Strong analytical and problemsolving skills Good communication More ❯