Design and ship reliable, scalable ML subsystems for a proactive AI assistant focusing on long-horizon workflows. Own the end-to-end process from data preparation and training to production deployment and iteration.
Remote Machine Learning Jobs (672)
Search = machine learning
Job category = Software Development
Design and ship reliable, scalable ML subsystems for a proactive AI assistant focusing on long-horizon workflows. Own the end-to-end lifecycle from data preparation and training to production inference and iteration.
Design and ship reliable, scalable ML subsystems for a proactive AI assistant focusing on long-horizon workflows. Own the end-to-end process from data preparation and training to production inference and iteration.
Detection Engineer - Machine Learning (Remote, East/Central)
CrowdStrike
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Full Time
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3 Weeks Ago
CrowdStrike
Analyze malware and detection data to improve machine learning model efficacy and manage false positives. Collaborate with internal teams to resolve customer inquiries regarding threat detections and binary legitimacy.
Design and implement optimization algorithms for auctions, bidding strategies, and pacing to balance advertiser performance and user experience. Own the end-to-end lifecycle of these systems from problem formulation and algorithm design to production deployment.
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Senior Manager, Machine Learning (Data Operations)
Coalition, Inc.
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Full Time
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3 Weeks Ago
Coalition, Inc.
Own the quality and methodology of data labeling across the organization, including designing annotation tasks and defining quality frameworks. Manage the Label Studio platform and oversee outsourced labeling vendors to ensure accurate and consistent datasets for production ML models.
Senior Manager, Machine Learning (Data Operations)
Coalition, Inc.
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Full Time
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3 Weeks Ago
Coalition, Inc.
Own the quality and methodology of labeled datasets used for production ML models, including designing annotation tasks and defining quality frameworks. Manage the Label Studio platform and oversee outsourced labeling vendors to ensure accuracy and throughput targets are met.
Design, build, and deploy backend generative AI solutions to power automated, intelligent workflows. Convert complex R&D problems into production-ready software while maintaining ownership of the machine learning architecture.
Define and build the architectural foundation for a self-service machine learning platform to enable Data Scientists to deploy and monitor models independently. Establish engineering standards, reusable tooling strategies, and a phased roadmap for the organization's ML infrastructure.
Own the full lifecycle of predictive models in production, including architecture, training pipelines, and inference infrastructure. Build and operate systems for search ranking, recommendations, and feed ordering while establishing model monitoring and retraining cadences.
Build and operate production ML and LLM systems to improve discovery, relevance, and efficiency for the Social Travel platform. This includes designing MCP servers, agent-facing APIs, and implementing RAG-based applications.
Founding Machine Learning Engineer (Recommendations + GenAI)
Gamingtec
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Full Time
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3 Weeks Ago
Gamingtec
Design and build the intelligence layer for products, focusing on recommendations, ranking, and GenAI workflows. Turn ambiguous product goals into production-ready ML systems and establish evaluation frameworks to measure business impact.
Design and deploy intelligent forecasting models and quotation automation agents using GCP-native services. Develop production ML pipelines and integrate model outputs into agentic workflows to drive operational efficiency.
Senior Machine Learning - AI Engineer (Remote)
The Home Depot
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Full Time
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3 Weeks Ago
The Home Depot
Design, build, and optimize production-grade Agentic AI systems and multi-agent workflows to drive business outcomes. Collaborate with cross-functional teams to transition AI concepts from prototype to scalable enterprise-ready products.
Lead and grow a team of engineers to build risk management features that improve the merchant experience and act as a product differentiator. Collaborate cross-functionally with product, infrastructure, and risk strategy teams to deliver high-quality technical systems and APIs.
Lead a team in building and optimizing the machine learning infrastructure that powers a drug discovery platform. You will collaborate cross-functionally to enable the scaling of AI/ML, LLM, and agentic systems across supercomputing and cloud environments.
Implement and productionalize cutting-edge ML algorithms for personalization to improve gaming KPIs like retention and revenue. Design experiments and A/B tests to optimize player experience and translate research findings into scalable code.
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Lead the development of cutting-edge deep learning models and Gen AI solutions to analyze autonomous vehicle behavior and automate high-volume workflows. Collaborate with cross-functional teams to define technical direction and align ML strategies with business objectives.
Collaborate with cross-functional teams to design, deploy, and maintain end-to-end machine learning solutions for clinical and operational problems. Perform advanced analytical techniques including statistical modeling and causal inference to uncover insights that improve patient care.
Define and execute the long-term ML technical vision for the Trust organization to combat fraud and ensure platform safety. Lead the design and productionization of scalable ML models and pipelines, including Agentic AI and anomaly detection.
The Senior ML Engineer will build and maintain reusable machine learning frameworks and feature stores to support revenue and cost optimization projects. They are responsible for implementing MLOps best practices, including automated CI/CD testing and production monitoring for model performance.
Design, build, and operate machine learning models across the full lifecycle from data exploration to deployment and monitoring. Responsibilities range from supporting development at entry-level to architecting pipelines and mentoring engineers at the senior level.
Own the end-to-end productization of pricing and underwriting models to automate the valuation of alternative assets. Optimize ML infrastructure on AWS to reduce costs and latency while improving model accuracy and coverage.
Design and build the ML platform infrastructure to move data science models from notebooks to production. Establish MLOps standards, manage model serving on AWS SageMaker, and implement automated retraining and monitoring pipelines.
Drive the development and implementation of cutting-edge ML algorithms and sophisticated models to build AI functionalities into Atlassian products. Lead technical direction, design system architectures, and mentor other ML engineers to realize AI's transformative potential.
Lead the technical strategy and architecture for AI-driven quality and evaluation systems using LLMs and agents. Drive the development of scalable systems to detect regressions and generate actionable product insights across the organization.
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Develop and implement an AI-based Real-Time Mesoscale Analysis (AI-RTMA) system to improve weather forecast quality for NOAA. This includes designing data pipelines and conducting reviews of state-of-the-art AI data assimilation methodologies.
The role involves researching and improving LLM behavior for real-time voice conversations through fine-tuning and rigorous experimentation. You will build evaluation frameworks and analyze production data to enhance model reliability, naturalness, and task completion.
Develop, deploy, and maintain predictive and optimization machine learning models to solve complex business challenges. Design feature engineering pipelines and utilize MLflow for model lifecycle management and production monitoring.
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