Lead the architecture and deployment of an enterprise-scale AI platform focusing on Generative AI, agentic systems, and RAG capabilities. Establish standards for model governance, security, and reliability while mentoring senior engineering staff.
Remote Machine Learning Jobs (672)
Search = machine learning
Job category = Software Development
The role involves building and deploying ML models to automate workflows, predict treatment delays, and manage the intelligence layer of the platform. Responsibilities include architecting LLM-powered workflows and maintaining data pipelines for structured and unstructured data.
Lead and develop a team of Machine Learning specialists to build and improve models that detect financial crime and fraud. Partner with cross-functional stakeholders to translate ambiguous fraud problems into reliable, high-impact ML controls.
Senior Machine Learning Engineer - Power Factors
Opportunities with AppDirect's Advisor Partners (Recruitment as a Service)
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Full Time
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8 Weeks Ago
Opportunities with AppDirect's Advisor Partners (Recruitment as a Service)
Lead the architecture and training of foundational time-series models for renewable energy assets, focusing on tokenization and scaling from PoC to production. Build and optimize distributed training infrastructure and collaborate with cross-functional teams to align model outputs with business value.
Staff Machine Learning Systems Engineer, Embeddings Platform
Reddit
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Full Time
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8 Weeks Ago
Reddit
Lead the technical direction and architecture of large-scale machine learning models and embeddings platforms to enhance Reddit's personalization. Collaborate cross-functionally to integrate ML models into key systems while mentoring senior and mid-level engineers.
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Translate cutting-edge research into production-ready machine learning systems for image and video processing. Own the full ML lifecycle from experimentation and training to deployment and scaling in cloud environments.
Build and operationalize scalable AI-enabled platforms and distributed systems to automate the compliance content lifecycle. Design reusable cloud-native services and establish engineering standards for CI/CD and production operations.
Design, develop, and deploy production-grade AI solutions focusing on Computer Vision and LLM-based workflows. Optimize ML inference pipelines and collaborate with stakeholders to shape technical architecture and product direction.
Machine Learning Engineer - New AI Initiatives
Torc Robotics
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Full Time
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8 Weeks Ago
Torc Robotics
Lead complex data science projects to improve manufacturing processes and develop machine learning workflows from analysis to embedded deployment. Define data ingestion and governance standards while providing technical leadership and mentoring to team members.
Architect and scale enterprise-grade machine learning infrastructure and deployment pipelines to support clinical initiatives. Drive MLOps strategy, mentor engineering teams, and ensure the reliability and compliance of mission-critical ML services.
Lead the development of advanced perception algorithms and sensor fusion techniques for industrial robotic welding systems. Provide technical leadership by mentoring junior engineers and contributing to the strategic direction of the company's robotics architecture.
Collaborate with Data Science teams to implement and integrate ML algorithms into production code. Focus on ensuring performance, scalability, and the application of coding best practices within Scrum teams.
Senior Machine Learning Engineer
ZoomInfo Technologies LLC
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Full Time
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8 Weeks Ago
ZoomInfo Technologies LLC
Build and scale large-scale recommendation systems and advanced NLP embedding models to enhance data intelligence. Architect MLOps/LLMOps infrastructure and design agentic workflows for automated web extraction and entity resolution.
Analyze banking transactions to detect and prevent fraud using graph-based transactional analysis and ML models. Develop production-ready Python code and integrate fraud detection algorithms into the company's protection platform.
Build and iterate on supervised machine learning models to predict ad campaign delivery outcomes, replacing a simulation-based engine. Partner with ML engineers to deploy these models at scale and collaborate with cross-functional teams to drive adoption of ML-driven forecasts.
Develop, deploy, and optimize machine learning and large language models to enhance customer experiences and internal workflows. Build AI agents and MLOps pipelines to streamline model training, evaluation, and scalability.
Design and optimize large-scale continual pre-training pipelines for VLM foundation models. Conduct research on integrating multimodal data streams and develop metrics to evaluate model performance in autonomous driving contexts.
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The role involves identifying high-value opportunities from data and building practical ML or heuristic solutions to improve developer workflows. You will own the end-to-end execution from data exploration and modeling to backend integration and productization.
Architect and implement advanced ML solutions, including recommendation engines and LLM integrations, to enhance guest and host experiences. Lead and mentor cross-functional teams of ML, Data, and Product engineers to drive AI applications in messaging and notifications.
Research Scientist- Geometry & Machine Learning
Foundation EGI
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Full Time
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8 Weeks Ago
Foundation EGI
Design and develop geometry processing and simulation algorithms for engineering applications. Build services for processing 2D/3D engineering data and implement post-training workflows for machine learning models.
The Senior Machine Learning Engineer will own search and recommendation systems for Sekai’s consumer product, focusing on content discovery and user engagement. Responsibilities include building models that determine user interactions and improving recommendation quality for various content types.
The role involves adhering to software development best practices and collaborating with senior machine learning teams. You will support project leaders in machine learning initiatives and engage in analytical processes related to AI solutions.
Lead the design, development, and deployment of sophisticated ML and GenAI models to optimize clinical trial workflows and patient engagement. Collaborate with cross-functional teams to build scalable production-level pipelines and mentor junior engineers on ML best practices.
Partner with PhD researchers to design and implement production-quality machine learning models for quantitative trading strategies. Develop and maintain complex data pipelines and extensible tools to accelerate the model development lifecycle.
Lead the technical vision for AI/ML to automate sales workflows and deploy AI-augmented selling tools. Partner with product and engineering teams to build production models that increase sales productivity and revenue.
Staff Machine Learning Engineer - ML Training Infrastructure
General Motors
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Full Time
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9 Weeks Ago
General Motors
Design and build scalable, high-performance AI/ML platform infrastructure to support advanced research and model development. Optimize distributed training workflows and resource utilization across heterogeneous hardware to reduce costs and improve performance.
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Senior Machine Learning Operations Engineer II (AI Native)
Life360
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Full Time
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9 Weeks Ago
Life360
Design and scale automated CI/CD and continuous training pipelines to reliably deploy and monitor machine learning models. Collaborate with cross-functional teams to optimize cloud-based ML infrastructure and ensure robust data lineage and governance.
Architect and operate data and training pipelines across cloud and cluster environments to improve the autonomous driving stack. Build and maintain distributed training, orchestration tooling, and metadata stores for evaluation workflows.
Design, build, and maintain robust AI pipelines for data processing, model training, and deployment. Develop MVP code for AI initiatives and collaborate with engineers to transition these into production-ready systems.
Staff Applied Machine Learning Engineer - Intelligent Data, Signals & Systems
Block
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Full Time
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9 Weeks Ago
Block
Build and operate production ML systems that transform customer behavior and product context into trusted signals for ranking, recommendations, and decisioning. Design signal contracts and own the end-to-end lifecycle of customer intelligence systems from feature generation to monitoring.
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