1 to 25 of 111 Remote Anomaly Detection Jobs

and unforgettable gaming experiences. As we continue to push the boundaries of technology, we are seeking a talented Staff Machine Learning Engineer specializing in Anomaly Detection to join our dynamic R&D team. We are on a mission to revolutionize our QA processes by developing cutting-edge … unique opportunity to contribute to a global effort in making our QA processes more efficient and effective. As a Staff Machine Learning Engineer in Anomaly Detection, you will be the technical lead in a research team focused on advancing our anomaly detection technology, driving … anomalies in game streams. Your expertise will help shape the future of gaming by ensuring high-quality player experiences. What you'll be doing: Anomaly Detection Development: Design, develop, and implement novel anomaly detection algorithms to automatically identify bugs and glitches in game streams. More ❯

and usage guidelines-promoting robust governance and transparency. Perform and guide model retraining, performance monitoring, and updates for complex production models (e.g., time series, anomaly detection, natural language processing, LLM-based text summarization), proactively addressing performance gaps. Collaborate closely with domain experts to capture critical business requirements … transform, and prepare data for model training and deployment. Evaluate, implement, and refine state-of-the-art algorithms-including foundational language models, object detection/classification, and time series analysis-to tackle advanced enterprise challenges. Ensure strict adherence to enterprise standards for metadata management, governance, and security, integrating … optimizing data pipelines or analytics solutions. Deep expertise in training, deploying, and maintaining a diverse range of AI/ML models-including time series, anomaly detection, and large-scale natural language processing-across multiple environments. Strong understanding of AI model lifecycle management, including comprehensive metadata governance, monitoring More ❯

native ML workflows. You'll work closely with data engineers, backend developers, and product leaders to embed ML across core features - from forecasting and anomaly detection to optimization and automated decision-making. Key Responsibilities: * Design and build serverless ML pipelines using AWS tools (Lambda, SageMaker, Step Functions … Develop, deploy, and monitor models in production (e.g., cost forecasting, anomaly detection, usage classification) * Collaborate on data ingestion and transformation with Snowflake, DBT, Airflow, and other pipeline tools * Work alongside backend engineers building APIs that serve model predictions and insights * Implement model observability, drift detection More ❯

native ML workflows. You'll work closely with data engineers, backend developers, and product leaders to embed ML across core features - from forecasting and anomaly detection to optimization and automated decision-making. Key Responsibilities: * Design and build serverless ML pipelines using AWS tools (Lambda, SageMaker, Step Functions … Develop, deploy, and monitor models in production (e.g., cost forecasting, anomaly detection, usage classification) * Collaborate on data ingestion and transformation with Snowflake, DBT, Airflow, and other pipeline tools * Work alongside backend engineers building APIs that serve model predictions and insights * Implement model observability, drift detection More ❯

native ML workflows. You'll work closely with data engineers, backend developers, and product leaders to embed ML across core features - from forecasting and anomaly detection to optimization and automated decision-making. Key Responsibilities: * Design and build serverless ML pipelines using AWS tools (Lambda, SageMaker, Step Functions … Develop, deploy, and monitor models in production (e.g., cost forecasting, anomaly detection, usage classification) * Collaborate on data ingestion and transformation with Snowflake, DBT, Airflow, and other pipeline tools * Work alongside backend engineers building APIs that serve model predictions and insights * Implement model observability, drift detection More ❯

native ML workflows. You'll work closely with data engineers, backend developers, and product leaders to embed ML across core features - from forecasting and anomaly detection to optimization and automated decision-making. Key Responsibilities: * Design and build serverless ML pipelines using AWS tools (Lambda, SageMaker, Step Functions … Develop, deploy, and monitor models in production (e.g., cost forecasting, anomaly detection, usage classification) * Collaborate on data ingestion and transformation with Snowflake, DBT, Airflow, and other pipeline tools * Work alongside backend engineers building APIs that serve model predictions and insights * Implement model observability, drift detection More ❯

native ML workflows. You'll work closely with data engineers, backend developers, and product leaders to embed ML across core features - from forecasting and anomaly detection to optimization and automated decision-making. Key Responsibilities: * Design and build serverless ML pipelines using AWS tools (Lambda, SageMaker, Step Functions … Develop, deploy, and monitor models in production (e.g., cost forecasting, anomaly detection, usage classification) * Collaborate on data ingestion and transformation with Snowflake, DBT, Airflow, and other pipeline tools * Work alongside backend engineers building APIs that serve model predictions and insights * Implement model observability, drift detection More ❯

native ML workflows. You'll work closely with data engineers, backend developers, and product leaders to embed ML across core features - from forecasting and anomaly detection to optimization and automated decision-making. Key Responsibilities: * Design and build serverless ML pipelines using AWS tools (Lambda, SageMaker, Step Functions … Develop, deploy, and monitor models in production (e.g., cost forecasting, anomaly detection, usage classification) * Collaborate on data ingestion and transformation with Snowflake, DBT, Airflow, and other pipeline tools * Work alongside backend engineers building APIs that serve model predictions and insights * Implement model observability, drift detection More ❯

native ML workflows. You'll work closely with data engineers, backend developers, and product leaders to embed ML across core features - from forecasting and anomaly detection to optimization and automated decision-making. Key Responsibilities: * Design and build serverless ML pipelines using AWS tools (Lambda, SageMaker, Step Functions … Develop, deploy, and monitor models in production (e.g., cost forecasting, anomaly detection, usage classification) * Collaborate on data ingestion and transformation with Snowflake, DBT, Airflow, and other pipeline tools * Work alongside backend engineers building APIs that serve model predictions and insights * Implement model observability, drift detection More ❯

native ML workflows. You'll work closely with data engineers, backend developers, and product leaders to embed ML across core features - from forecasting and anomaly detection to optimization and automated decision-making. Key Responsibilities: * Design and build serverless ML pipelines using AWS tools (Lambda, SageMaker, Step Functions … Develop, deploy, and monitor models in production (e.g., cost forecasting, anomaly detection, usage classification) * Collaborate on data ingestion and transformation with Snowflake, DBT, Airflow, and other pipeline tools * Work alongside backend engineers building APIs that serve model predictions and insights * Implement model observability, drift detection More ❯

native ML workflows. You'll work closely with data engineers, backend developers, and product leaders to embed ML across core features - from forecasting and anomaly detection to optimization and automated decision-making. Key Responsibilities: * Design and build serverless ML pipelines using AWS tools (Lambda, SageMaker, Step Functions … Develop, deploy, and monitor models in production (e.g., cost forecasting, anomaly detection, usage classification) * Collaborate on data ingestion and transformation with Snowflake, DBT, Airflow, and other pipeline tools * Work alongside backend engineers building APIs that serve model predictions and insights * Implement model observability, drift detection More ❯

native ML workflows. You'll work closely with data engineers, backend developers, and product leaders to embed ML across core features - from forecasting and anomaly detection to optimization and automated decision-making. Key Responsibilities: * Design and build serverless ML pipelines using AWS tools (Lambda, SageMaker, Step Functions … Develop, deploy, and monitor models in production (e.g., cost forecasting, anomaly detection, usage classification) * Collaborate on data ingestion and transformation with Snowflake, DBT, Airflow, and other pipeline tools * Work alongside backend engineers building APIs that serve model predictions and insights * Implement model observability, drift detection More ❯

native ML workflows. You'll work closely with data engineers, backend developers, and product leaders to embed ML across core features - from forecasting and anomaly detection to optimization and automated decision-making. Key Responsibilities: * Design and build serverless ML pipelines using AWS tools (Lambda, SageMaker, Step Functions … Develop, deploy, and monitor models in production (e.g., cost forecasting, anomaly detection, usage classification) * Collaborate on data ingestion and transformation with Snowflake, DBT, Airflow, and other pipeline tools * Work alongside backend engineers building APIs that serve model predictions and insights * Implement model observability, drift detection More ❯

native ML workflows. You'll work closely with data engineers, backend developers, and product leaders to embed ML across core features - from forecasting and anomaly detection to optimization and automated decision-making. Key Responsibilities: * Design and build serverless ML pipelines using AWS tools (Lambda, SageMaker, Step Functions … Develop, deploy, and monitor models in production (e.g., cost forecasting, anomaly detection, usage classification) * Collaborate on data ingestion and transformation with Snowflake, DBT, Airflow, and other pipeline tools * Work alongside backend engineers building APIs that serve model predictions and insights * Implement model observability, drift detection More ❯

native ML workflows. You'll work closely with data engineers, backend developers, and product leaders to embed ML across core features - from forecasting and anomaly detection to optimization and automated decision-making. Key Responsibilities: * Design and build serverless ML pipelines using AWS tools (Lambda, SageMaker, Step Functions … Develop, deploy, and monitor models in production (e.g., cost forecasting, anomaly detection, usage classification) * Collaborate on data ingestion and transformation with Snowflake, DBT, Airflow, and other pipeline tools * Work alongside backend engineers building APIs that serve model predictions and insights * Implement model observability, drift detection More ❯

native ML workflows. You'll work closely with data engineers, backend developers, and product leaders to embed ML across core features - from forecasting and anomaly detection to optimization and automated decision-making. Key Responsibilities: * Design and build serverless ML pipelines using AWS tools (Lambda, SageMaker, Step Functions … Develop, deploy, and monitor models in production (e.g., cost forecasting, anomaly detection, usage classification) * Collaborate on data ingestion and transformation with Snowflake, DBT, Airflow, and other pipeline tools * Work alongside backend engineers building APIs that serve model predictions and insights * Implement model observability, drift detection More ❯

native ML workflows. You'll work closely with data engineers, backend developers, and product leaders to embed ML across core features - from forecasting and anomaly detection to optimization and automated decision-making. Key Responsibilities: * Design and build serverless ML pipelines using AWS tools (Lambda, SageMaker, Step Functions … Develop, deploy, and monitor models in production (e.g., cost forecasting, anomaly detection, usage classification) * Collaborate on data ingestion and transformation with Snowflake, DBT, Airflow, and other pipeline tools * Work alongside backend engineers building APIs that serve model predictions and insights * Implement model observability, drift detection More ❯

native ML workflows. You'll work closely with data engineers, backend developers, and product leaders to embed ML across core features - from forecasting and anomaly detection to optimization and automated decision-making. Key Responsibilities: * Design and build serverless ML pipelines using AWS tools (Lambda, SageMaker, Step Functions … Develop, deploy, and monitor models in production (e.g., cost forecasting, anomaly detection, usage classification) * Collaborate on data ingestion and transformation with Snowflake, DBT, Airflow, and other pipeline tools * Work alongside backend engineers building APIs that serve model predictions and insights * Implement model observability, drift detection More ❯

native ML workflows. You'll work closely with data engineers, backend developers, and product leaders to embed ML across core features - from forecasting and anomaly detection to optimization and automated decision-making. Key Responsibilities: * Design and build serverless ML pipelines using AWS tools (Lambda, SageMaker, Step Functions … Develop, deploy, and monitor models in production (e.g., cost forecasting, anomaly detection, usage classification) * Collaborate on data ingestion and transformation with Snowflake, DBT, Airflow, and other pipeline tools * Work alongside backend engineers building APIs that serve model predictions and insights * Implement model observability, drift detection More ❯

native ML workflows. You'll work closely with data engineers, backend developers, and product leaders to embed ML across core features - from forecasting and anomaly detection to optimization and automated decision-making. Key Responsibilities: * Design and build serverless ML pipelines using AWS tools (Lambda, SageMaker, Step Functions … Develop, deploy, and monitor models in production (e.g., cost forecasting, anomaly detection, usage classification) * Collaborate on data ingestion and transformation with Snowflake, DBT, Airflow, and other pipeline tools * Work alongside backend engineers building APIs that serve model predictions and insights * Implement model observability, drift detection More ❯

native ML workflows. You'll work closely with data engineers, backend developers, and product leaders to embed ML across core features - from forecasting and anomaly detection to optimization and automated decision-making. Key Responsibilities: * Design and build serverless ML pipelines using AWS tools (Lambda, SageMaker, Step Functions … Develop, deploy, and monitor models in production (e.g., cost forecasting, anomaly detection, usage classification) * Collaborate on data ingestion and transformation with Snowflake, DBT, Airflow, and other pipeline tools * Work alongside backend engineers building APIs that serve model predictions and insights * Implement model observability, drift detection More ❯

native ML workflows. You'll work closely with data engineers, backend developers, and product leaders to embed ML across core features - from forecasting and anomaly detection to optimization and automated decision-making. Key Responsibilities: * Design and build serverless ML pipelines using AWS tools (Lambda, SageMaker, Step Functions … Develop, deploy, and monitor models in production (e.g., cost forecasting, anomaly detection, usage classification) * Collaborate on data ingestion and transformation with Snowflake, DBT, Airflow, and other pipeline tools * Work alongside backend engineers building APIs that serve model predictions and insights * Implement model observability, drift detection More ❯

native ML workflows. You'll work closely with data engineers, backend developers, and product leaders to embed ML across core features - from forecasting and anomaly detection to optimization and automated decision-making. Key Responsibilities: * Design and build serverless ML pipelines using AWS tools (Lambda, SageMaker, Step Functions … Develop, deploy, and monitor models in production (e.g., cost forecasting, anomaly detection, usage classification) * Collaborate on data ingestion and transformation with Snowflake, DBT, Airflow, and other pipeline tools * Work alongside backend engineers building APIs that serve model predictions and insights * Implement model observability, drift detection More ❯

native ML workflows. You'll work closely with data engineers, backend developers, and product leaders to embed ML across core features - from forecasting and anomaly detection to optimization and automated decision-making. Key Responsibilities: * Design and build serverless ML pipelines using AWS tools (Lambda, SageMaker, Step Functions … Develop, deploy, and monitor models in production (e.g., cost forecasting, anomaly detection, usage classification) * Collaborate on data ingestion and transformation with Snowflake, DBT, Airflow, and other pipeline tools * Work alongside backend engineers building APIs that serve model predictions and insights * Implement model observability, drift detection More ❯

native ML workflows. You'll work closely with data engineers, backend developers, and product leaders to embed ML across core features - from forecasting and anomaly detection to optimization and automated decision-making. Key Responsibilities: * Design and build serverless ML pipelines using AWS tools (Lambda, SageMaker, Step Functions … Develop, deploy, and monitor models in production (e.g., cost forecasting, anomaly detection, usage classification) * Collaborate on data ingestion and transformation with Snowflake, DBT, Airflow, and other pipeline tools * Work alongside backend engineers building APIs that serve model predictions and insights * Implement model observability, drift detection More ❯