1 to 25 of 10,478 Remote Machine Learning Jobs

with machine learning techniques. Always with an ethical and accurate lens. A Machine Learning & AI Engineer designing and deploying robust ML systems that bring data science to life through automation, CI/CD, and modern cloud engineering practices. Wherever you land, youll be working with some … models for fraud detection, credit risk, customer segmentation, and behavioural analytics using scalable frameworks like TensorFlow, PyTorch, and XGBoost. Engineer robust data pipelines and ML workflows using Apache Spark, Vertex AI, and CI/CD tooling to ensure seamless model delivery and monitoring. Apply advanced techniques in deep learning ...

with machine learning techniques. Always with an ethical and accurate lens. A Machine Learning & AI Engineer designing and deploying robust ML systems that bring data science to life through automation, CI/CD, and modern cloud engineering practices. Wherever you land, youll be working with some … models for fraud detection, credit risk, customer segmentation, and behavioural analytics using scalable frameworks like TensorFlow, PyTorch, and XGBoost. Engineer robust data pipelines and ML workflows using Apache Spark, Vertex AI, and CI/CD tooling to ensure seamless model delivery and monitoring. Apply advanced techniques in deep learning ...

with machine learning techniques. Always with an ethical and accurate lens. A Machine Learning & AI Engineer designing and deploying robust ML systems that bring data science to life through automation, CI/CD, and modern cloud engineering practices. Wherever you land, youll be working with some … models for fraud detection, credit risk, customer segmentation, and behavioural analytics using scalable frameworks like TensorFlow, PyTorch, and XGBoost. Engineer robust data pipelines and ML workflows using Apache Spark, Vertex AI, and CI/CD tooling to ensure seamless model delivery and monitoring. Apply advanced techniques in deep learning ...

with machine learning techniques. Always with an ethical and accurate lens. A Machine Learning & AI Engineer designing and deploying robust ML systems that bring data science to life through automation, CI/CD, and modern cloud engineering practices. Wherever you land, youll be working with some … models for fraud detection, credit risk, customer segmentation, and behavioural analytics using scalable frameworks like TensorFlow, PyTorch, and XGBoost. Engineer robust data pipelines and ML workflows using Apache Spark, Vertex AI, and CI/CD tooling to ensure seamless model delivery and monitoring. Apply advanced techniques in deep learning ...

make insurance and financial services easier to access, understand, and afford for millions of users. As a Senior AI/ML Software Engineer, you'll help build the intelligent systems that power this mission - from personalized recommendations and fraud detection to automation and search. This is a fully remote role … contribute to production grade AI systems that support millions of users You'll collaborate across product, data, and engineering to build scalable ML tools end to end You'll grow quickly in a lean, high impact environment What You'll Do Work with product, data, and engineering teams to define ...

problems with machine learning techniques. Always with an ethical and accurate lens. A Machine Learning & AI Engineerdesigning and deploying robust ML systems that bring data science to life through automation, CI/CD, and modern cloud engineering practices. Wherever you land, youll be working with some … models for fraud detection, credit risk, customer segmentation, and behavioural analytics using scalable frameworks like TensorFlow, PyTorch, and XGBoost. Engineer robust data pipelines and ML workflows using Apache Spark, Vertex AI, and CI/CD tooling to ensure seamless model delivery and monitoring. Apply advanced techniques in deep learning ...

problems with machine learning techniques. Always with an ethical and accurate lens. A Machine Learning & AI Engineerdesigning and deploying robust ML systems that bring data science to life through automation, CI/CD, and modern cloud engineering practices. Wherever you land, youll be working with some … models for fraud detection, credit risk, customer segmentation, and behavioural analytics using scalable frameworks like TensorFlow, PyTorch, and XGBoost. Engineer robust data pipelines and ML workflows using Apache Spark, Vertex AI, and CI/CD tooling to ensure seamless model delivery and monitoring. Apply advanced techniques in deep learning ...

problems with machine learning techniques. Always with an ethical and accurate lens. A Machine Learning & AI Engineerdesigning and deploying robust ML systems that bring data science to life through automation, CI/CD, and modern cloud engineering practices. Wherever you land, youll be working with some … models for fraud detection, credit risk, customer segmentation, and behavioural analytics using scalable frameworks like TensorFlow, PyTorch, and XGBoost. Engineer robust data pipelines and ML workflows using Apache Spark, Vertex AI, and CI/CD tooling to ensure seamless model delivery and monitoring. Apply advanced techniques in deep learning ...

role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working … collaboration with the Product and Data Science teams. Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation). Solve complex problems by writing and testing application code ...

role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working … collaboration with the Product and Data Science teams. Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation). Solve complex problems by writing and testing application code ...

services, Snowflake-based data platform), following clean code and DevOps practices (Git, CI/CD, testing). Use and further develop data-driven and ML-inspired approaches (e.g. time series models, tree-based models, regularization, feature engineering) where they add value to risk management and pricing. Closely collaborate with Trading … time series analysis; familiarity with derivative pricing, valuation and risk metrics (e.g. VaR, ES, sensitivities) is highly welcome. Practical exposure to data-driven/ML techniques for forecasting, scenario generation or model calibration is a plus. Experience working with databases and cloud/data platforms (SQL, Snowflake, Azure, or similar ...

complex datasets to drive strategic decision-making. Collaborating closely with various subject matter experts across various fields, our team leverages advanced statistical analysis, machine learning techniques, and data visualization tools to uncover patterns, trends, and correlations within the data. Additionally, we are dedicated to delivering new, innovative capabilities … innovative global capabilities and driving AI fluency in the anchor markets ( majorly EU ). This includes leading the execution and interpretation of AI/ML models, framing problems, and shaping solutions with clear and compelling communication of data-driven insights. This role is dynamic, require consulting experience to drive ...

complex datasets to drive strategic decision-making. Collaborating closely with various subject matter experts across various fields, our team leverages advanced statistical analysis, machine learning techniques, and data visualization tools to uncover patterns, trends, and correlations within the data. Additionally, we are dedicated to delivering new, innovative capabilities … innovative global capabilities and driving AI fluency in the anchor markets ( majorly EU ). This includes leading the execution and interpretation of AI/ML models, framing problems, and shaping solutions with clear and compelling communication of data-driven insights. This role is dynamic, require consulting experience to drive ...

services, Snowflake-based data platform), following clean code and DevOps practices (Git, CI/CD, testing). Use and further develop data-driven and ML-inspired approaches (e.g. time series models, tree-based models, regularization, feature engineering) where they add value to risk management and pricing. Closely collaborate with Trading … time series analysis; familiarity with derivative pricing, valuation and risk metrics (e.g. VaR, ES, sensitivities) is highly welcome. Practical exposure to data-driven/ML techniques for forecasting, scenario generation or model calibration is a plus. Experience working with databases and cloud/data platforms (SQL, Snowflake, Azure, or similar ...

services, Snowflake-based data platform), following clean code and DevOps practices (Git, CI/CD, testing). Use and further develop data-driven and ML-inspired approaches (e.g. time series models, tree-based models, regularization, feature engineering) where they add value to risk management and pricing. Closely collaborate with Trading … time series analysis; familiarity with derivative pricing, valuation and risk metrics (e.g. VaR, ES, sensitivities) is highly welcome. Practical exposure to data-driven/ML techniques for forecasting, scenario generation or model calibration is a plus. Experience working with databases and cloud/data platforms (SQL, Snowflake, Azure, or similar ...

services, Snowflake-based data platform), following clean code and DevOps practices (Git, CI/CD, testing). Use and further develop data-driven and ML-inspired approaches (e.g. time series models, tree-based models, regularization, feature engineering) where they add value to risk management and pricing. Closely collaborate with Trading … time series analysis; familiarity with derivative pricing, valuation and risk metrics (e.g. VaR, ES, sensitivities) is highly welcome. Practical exposure to data-driven/ML techniques for forecasting, scenario generation or model calibration is a plus. Experience working with databases and cloud/data platforms (SQL, Snowflake, Azure, or similar ...

services, Snowflake-based data platform), following clean code and DevOps practices (Git, CI/CD, testing). Use and further develop data-driven and ML-inspired approaches (e.g. time series models, tree-based models, regularization, feature engineering) where they add value to risk management and pricing. Closely collaborate with Trading … time series analysis; familiarity with derivative pricing, valuation and risk metrics (e.g. VaR, ES, sensitivities) is highly welcome. Practical exposure to data-driven/ML techniques for forecasting, scenario generation or model calibration is a plus. Experience working with databases and cloud/data platforms (SQL, Snowflake, Azure, or similar ...

engineering roadmap, but how they fundamentally approach solving complex, real-world security challenges with data. You'll work at the intersection of data science, ML infrastructure, and product innovation, leading efforts to build and evolve ML-driven capabilities, while also ensuring the reliability and scalability of their models in production … understanding behaviour patterns and identifying cybersecurity anomalies. Partner with product, engineering, and domain experts to translate strategic goals and customer needs into practical, scalable ML solutions. Drive model development end-to-end, from exploratory analysis, feature design, and prototyping to validation and deployment. Collaborate with platform and infra teams ...

there are no surprises Building things that actually work Once the problem and value are clear, you will design and deliver production ready ML and GenAI solutions. That includes: Designing and building data pipelines, batch or streaming, that support the desired outcomes Working with engineers and architects so your work … protect value over time: Experiment tracking and model versioning so you know what works and can roll back safely CI/CD pipelines for ML so improvements reach users quickly and reliably Monitoring and alerting for models and data so you can catch issues before they damage trust or results ...

unstructured data. Define and implement a unified data and metrics framework to ensure consistent definitions and understanding of KPIs across the organization. Data/ML Operations: Establish and lead the design of CI/CD processes and tooling for data pipelines, enabling scalable, automated, and high-quality delivery across environments. … Vertex AI platform, including Vertex AI Pipelines, Model Registry, and Vertex AI Endpoints. Experience building the infrastructure that facilitates deployment and production tuning of ML models and AI systems (including LLMs). GCP Professional Data Engineer or Professional Machine Learning Engineer certifications. Why join us? Become part ...

unstructured data. Define and implement a unified data and metrics framework to ensure consistent definitions and understanding of KPIs across the organization. Data/ML Operations: Establish and lead the design of CI/CD processes and tooling for data pipelines, enabling scalable, automated, and high-quality delivery across environments. … Vertex AI platform, including Vertex AI Pipelines, Model Registry, and Vertex AI Endpoints. Experience building the infrastructure that facilitates deployment and production tuning of ML models and AI systems (including LLMs). GCP Professional Data Engineer or Professional Machine Learning Engineer certifications. Why join us? Become part ...

experience with Distributed data/computing tools (MapReduce, Hadoop, Hive, EMR, Kafka, Spark, Gurobi, or MySQL) 3+ years of experience with industry recognized ML frameworks such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 3+ years of experience building production-ready data pipelines that feed ML models 3+ years … experience building, scaling, and optimizing ML systems 2+ years of experience leading teams developing ML solutions 3+ years of experience with AWS, GCP, Azure, or another cloud service 4+ years of experience in open source frameworks 7+ years of people management experience 2+ years of experience in Agile practices ...

experience with Distributed data/computing tools (MapReduce, Hadoop, Hive, EMR, Kafka, Spark, Gurobi, or MySQL) 3+ years of experience with industry recognized ML frameworks such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 3+ years of experience building production-ready data pipelines that feed ML models 3+ years … experience building, scaling, and optimizing ML systems 2+ years of experience leading teams developing ML solutions 3+ years of experience with AWS, GCP, Azure, or another cloud service 4+ years of experience in open source frameworks 7+ years of people management experience 2+ years of experience in Agile practices ...

Python or .NET with generative AI capabilities. Solid experience in any of the following: Azure AI Foundry (Models, Agent Service, Semantic Kernel, Search, ML, SDK) Copilot Studio AppPlat/Containers/Serverless (App Service, AKS, ACA, ARO, Functions) Azure Integration Service (APIM, Logic Apps) DevOps (CI/CD, Azure DevOps ...

focus on exciting Data and AI topics. Find sample projects in our Motius Success Stories. Your Role Solutions/Delivery Architect with focus on Machine Learning (m/f/d) in our R&D projects with engineering teams of 2-5 people Designing and building real … customer engagements Strong background in machine learning, deep learning, data science, and algorithmic problem solving Proven experience in data engineering and ML engineering pipelines, and technologies as well as with cloud platforms (Azure, AWS or GCP), ideally across data & AI stacks Proficiency in Python and SQL; additional ...