Design, build, and deploy advanced machine learning systems for various use cases while collaborating with cross-functional teams. Lead model development across the ML lifecycle and drive experimentation tied to business outcomes.
Remote Machine Learning Jobs (628)
Search = machine learning
Job category = Software Development
The Machine Learning Engineer will design, develop, and optimize Retrieval-Augmented Generation (RAG) models to solve complex problems for clients. They will collaborate with client teams to deploy these models into production environments and ensure their long-term success.
The Senior Platform Engineer will design, build, and maintain the infrastructure and tools for training, evaluating, deploying, and serving Machine Learning models. They will collaborate with ML teams to identify needs and create solutions.
The Senior Platform Engineer will design, build, and maintain the infrastructure and tools for training, evaluating, deploying, and serving Machine Learning models. They will collaborate with ML teams to identify needs and create solutions.
Machine Learning Engineer, Marketplace Optimization
DoorDash USA
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Full Time
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20 Weeks Ago
DoorDash USA
Design, build, and deploy ML models and pipelines for pacing, bidding, auction, and targeting optimization. Collaborate with Data Science and Product teams to develop and evaluate new algorithms through rigorous experimentation.
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The team is responsible for designing, building, and maintaining the infrastructure and tools that enable other teams to train, evaluate, deploy, and serve Machine Learning models and features at scale. This involves working closely with ML teams to identify needs and build magically simple solutions using backend engineering experience.
The engineer will join a Research and Development team to create new features for potential products by analyzing state-of-the-art architectures and proposing new Proof of Concept projects. Responsibilities include building these Proof of Concepts from scratch, implementing algorithms for research support, and optimizing existing implementations for core product development.
AI / Machine Learning Engineer
CyberMedia Technologies
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Full Time
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20 Weeks Ago
CyberMedia Technologies
As an AI/ML Engineer, you will develop AI systems to automate health benefits determinations for the Office of Personnel Management. Your role will involve designing autonomous AI agents and integrating deterministic logic to ensure compliance with federal regulations.
The MLOps Engineer will design, deploy, and maintain scalable and ethical autonomous AI systems. Key tasks include model deployment, cloud infrastructure management, automation of workflows, and ensuring compliance with security and ethical standards.
You will build and maintain foundational AI gateways and inference services for Kraken, ensuring reliable access to ML and generative AI models. Additionally, you will architect internal evaluation tooling and act as a technical mentor for other teams.
Machine Learning Engineer (Remote)
Triumph Financial, Inc.
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Full Time
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20 Weeks Ago
Triumph Financial, Inc.
The Machine Learning Engineer will work closely in a small, cross-functional team focused on AI/ML systems, taking ownership of projects from ideation to deployment. They will collaborate with product managers and stakeholders to understand customer pain points and deliver impactful solutions.
![Smart Working Solutions is hiring for remote Machine Learning Engineer (Remote, Full-Time) [HR141]](/assets/08150176-369d-44db-a4a7-778571334971.png){kind=small}
Machine Learning Engineer (Remote, Full-Time) [HR141]
Smart Working Solutions
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Full Time
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21 Weeks Ago
Smart Working Solutions
The Machine Learning Engineer will enable the Pricing and Analytics function to deliver value through standardized workflows and maintain Python-based modeling and ML tooling. They will also collaborate with various teams to ensure that the tooling meets business needs.
Machine Learning Engineer (m/w/d)
PROFI Engineering Systems AG
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Full Time
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21 Weeks Ago
PROFI Engineering Systems AG
The role involves self-organized work within an agile SCRUM team, focusing on the development of AI-based cloud solutions for predictive maintenance. Responsibilities include technical implementation, training, quality assurance, and ensuring smooth operations in a modern cloud and Kubernetes environment.
Design and implement knowledge distillation pipelines and distill large foundation models into smaller, faster models for inference. Run large-scale training experiments and collaborate with research to translate new ideas into production-ready code.
Participants will engage in a rigorous, full-time training program that includes working on capstone projects based on real-world problems. They will receive feedback and mentorship to prepare for high-impact AI projects with top-tier clients.
Lead machine learning efforts across Hightouch, focusing on product development and improving execution pace. Foster team growth and ensure high reliability in operations.
Research Assistant/Research Associate/Research Engineer II (Remote Sensing and Machine Learning)
Nanyang Technological University Singapore
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Full Time
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21 Weeks Ago
Nanyang Technological University Singapore
The researcher will perform fieldwork and curate remote sensing data, develop algorithms for biodiversity classification and LIDAR canopy analysis, and construct a professional data portal for stakeholders. They will also liaise between NTU, NUS, and NParks to ensure project success.
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Machine Learning Architect - Not an Active Opening, Building Talent Pipeline
Caylent
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Full Time
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22 Weeks Ago
Caylent
The Machine Learning Architect will guide teams through Agile ceremonies and translate customer requirements into actionable tasks for engineers. They will also lead discussions on architecture and ensure the delivery of high-quality cloud native applications on AWS.
The Staff Machine Learning Engineer will craft, implement, and maintain MLOps tools and practices while optimizing model performance and scalability. They will also build tools to improve the lives of data scientists and contribute to the design and architecture of ML systems.
Senior Machine Learning Engineer, Cybersecurity / Threat Detection
Keeper Security
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Full Time
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22 Weeks Ago
Keeper Security
You will design and maintain datasets for training threat detection models and build custom ML models for threat classification. The role also involves developing inference services and integrating AI/ML capabilities for real-time analysis.
You will be responsible for training, evaluation, and deployment of ML-based models for scene understanding and behavior prediction. This includes designing experiments, implementing metrics, and releasing model updates.
The Lead Machine Learning Engineer will build, train, and deploy ML models to enhance product performance and monetization. They will also collaborate with various teams and work on projects involving LLMs and Generative AI technologies.
The role involves completing AI training tasks, analyzing and editing annotations, and judging AI performance on ML-relevant tasks. Additionally, the specialist will provide expert feedback to improve AI models.
AI Training - Machine Learning Specialist (EST) 112 APPLICANTS
Prolific
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Full Time
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23 Weeks Ago
Prolific
The role involves completing AI training tasks, analyzing and editing annotations, and judging AI performance on ML-relevant tasks. Additionally, you will provide expert feedback to improve AI models.
AI Training - Machine Learning Specialist (PST) 43 APPLICANTS
Prolific
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Full Time
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23 Weeks Ago
Prolific
The role involves completing AI training tasks such as analyzing and writing annotations, and judging the performance of AI in ML-relevant tasks. Additionally, you will provide expert feedback to improve AI models.
Senior Machine Learning Engineer - Not an Active Opening, Building Talent Pipeline
Caylent
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Full Time
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23 Weeks Ago
Caylent
The Senior Machine Learning Engineer will work as part of a cross-functional delivery team to design and document machine learning solutions on the AWS cloud for customers. Responsibilities include developing and implementing ML models, MLOps, and analytics.
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Machine Learning Architect - Not an Active Opening, Building Talent Pipeline
Caylent
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Full Time
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23 Weeks Ago
Caylent
The Machine Learning Architect will guide teams through Agile ceremonies and translate customer requirements into actionable tasks for engineers. They will also lead discussions on architecture and troubleshoot issues in various environments.
You will develop end-to-end AI solutions, participating in the entire lifecycle from understanding business problems to deploying and monitoring models in production. You will also design and develop robust ML pipelines and architectures while mentoring teams and interacting with clients to translate their needs into impactful AI solutions.
Machine Learning Architect - Not an Active Opening, Building Talent Pipeline
Caylent
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Full Time
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23 Weeks Ago
Caylent
The Machine Learning Architect will guide teams through Agile ceremonies and translate customer requirements into actionable tasks for engineers. They will also lead discussions on architecture and ensure the delivery of high-quality cloud native applications on AWS.
As a Principal Solutions Architect, you will architect end-to-end AI/ML solutions and lead a team to build platforms that meet customer requirements. You will also engage with clients to understand their AI/ML goals and drive account growth.
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