Lead the development and ownership of the machine learning systems powering the Personalization Engine within Cedar Pay. This includes managing ML engineers and executing the full ML lifecycle from modeling to high-performance MLOps.
Remote Machine Learning Jobs (672)
Search = machine learning
Job category = Software Development
Lead the technical strategy and architecture for ads identity modeling and measurement solutions. Oversee end-to-end ML workflows and partner with cross-functional teams to define the long-term roadmap.
Own the full machine learning lifecycle from problem discovery and design to deployment and monitoring of ML-powered features. Collaborate with cross-functional teams to implement models that improve customer experience and business growth.
Design, develop, and deploy scalable LLM-powered systems and agentic pipelines to enhance real estate operations and customer experience. Collaborate across departments to integrate AI solutions into product development and maintain production-grade AI architectures.
Senior Machine Learning Engineer (AI tools)
SmartRecruiters Inc
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Full Time
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13 Weeks Ago
SmartRecruiters Inc
Architect and build agentic workflows and conversational systems using LLMs and reasoning components to optimize recruiting. Lead the end-to-end development of ML/NLP products from ideation through production and deployment.
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Develop large-scale, fault-tolerant multimodal agentic experiences and interaction modes like Voice AI and Deep Research. Lead complex, multi-team initiatives while establishing robust evaluation frameworks and safety guardrails for AI agents.
You will build and improve core machine learning components across data, training, evaluation, and inference pipelines. Additionally, you will debug production issues and iterate on models to meet strict reliability, latency, and cost targets.
You will own the end-to-end development of critical ML subsystems, including data preparation, training, and production deployment. You will collaborate with research and engineering teams to build reliable, scalable AI systems that meet performance and latency targets.
You will be responsible for building and owning end-to-end machine learning pipelines, including training, evaluation, inference, and production deployment. You will collaborate with research and application teams to integrate scalable, high-performance AI systems into products.
You will define the research direction for A1's core intelligence, focusing on reasoning, memory, planning, and orchestration. You will also establish evaluation frameworks to ensure real-world usefulness, safety, and robustness of the AI system.
The Senior Machine Learning Engineer will lead the end-to-end development and lifecycle management of machine learning models using proprietary data. Responsibilities include building scalable production-grade systems, collaborating with cross-functional teams, and ensuring model performance through continuous monitoring and improvement.
Design and build scalable training and inference systems for LLMs, Multimodal LLMs, and other media ML models. Optimize end-to-end training and inference serving to improve scalability, latency, and reliability across global workloads.
AI Senior Machine Learning Engineer -Gen AI, Machine Learning, Graph ML (10189)
Extreme Networks
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Full Time
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14 Weeks Ago
Extreme Networks
Lead the end-to-end software development lifecycle for AI-driven networking solutions, including design, implementation, and deployment of high-performance microservices. Mentor engineering team members while driving technical strategy and innovation in Generative AI and multi-agent systems.
Design, build, and deploy end-to-end predictive models while managing the full machine learning lifecycle. Collaborate with domain experts to translate research literature into production-grade systems that handle complex biological data.
The Senior Machine Learning Engineer will lead technical initiatives, mentor team members, and design end-to-end predictive models for biological data. They are responsible for the full machine learning lifecycle, from research and prototyping to production deployment and monitoring.
You will lead the design, development, and productionization of machine learning models to drive user acquisition, activation, and retention. You will own the full model lifecycle and collaborate with cross-functional teams to identify high-impact growth opportunities.
Senior Machine Learning Engineer (Tech Lead), Robot Learning, Loco- Manipulation
Path Robotics
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Full Time
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14 Weeks Ago
Path Robotics
You will set the technical direction for the robot learning team, designing architectures for perception, reasoning, and action generation. Additionally, you will mentor junior engineers and drive the deployment strategy for complex loco-manipulation systems.
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You will design, train, and deploy computer vision models while owning the full machine learning pipeline from data preprocessing to production. You will also collaborate with cross-functional teams to integrate these solutions into the platform and establish observability benchmarks.
Senior Machine Learning Developer, Advertiser Growth | Développeur(euse) principal(e) en apprentissage machine, Advertiser Growth
Unity Technologies
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Full Time
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15 Weeks Ago
Unity Technologies
You will architect GenAI systems for creative asset generation and design sophisticated budget pacing algorithms to manage marketplace spend. Additionally, you will build high-velocity experimentation infrastructure and maintain high-throughput billing pipelines to ensure financial integrity.
You will design and build production-grade agent systems, including planning, tool execution, and reasoning pipelines. Additionally, you will own the reliability, observability, and evaluation frameworks to ensure high-quality agent performance and continuous model improvement.
Develop machine learning models to automate the generation of scientifically accurate, editable visuals from research inputs. Implement natural language-based editing tools to enable intuitive figure creation while maintaining scientific integrity.
Lead a team of machine learning engineers to design and deploy high-impact fraud detection models across the full ML lifecycle. Define technical strategy and collaborate cross-functionally to integrate models into decisioning systems while driving the adoption of advanced modeling techniques.
You will lead a team of machine learning engineers to design and deploy high-impact fraud detection models across the full ML lifecycle. Additionally, you will define the technical strategy and partner cross-functionally to integrate these models into decisioning systems.
Lead the design and implementation of Reddit's next-generation user understanding initiative by building unified, high-fidelity user representations. Drive technical strategy across personalization surfaces like Feeds, Search, and Ads while mentoring senior staff and ensuring system scalability.
Evaluate and analyze LLM performance while architecting and building inference and training pipelines. You will contribute to hands-on design, model training, and deployment strategies within a technical greenfield project.
(Senior) Consultant Machine Learning (m/w/d)
Blueforte GmbH
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Full Time
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15 Weeks Ago
Blueforte GmbH
You will develop and optimize machine learning and deep learning models while creating modern analytics architectures for clients. Additionally, you will manage the entire development lifecycle from conceptualization and validation to implementation and maintenance of AI solutions.
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Senior Machine Learning Engineer (AI tools)
SmartRecruiters Inc
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Full Time
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15 Weeks Ago
SmartRecruiters Inc
You will architect and develop agentic workflows that integrate large language models and reasoning components to create adaptive conversational systems. Additionally, you will lead the end-to-end development of ML/NLP products, from ideation and model training to production deployment.
Manage and mentor a team of data scientists to develop and maintain fraud detection models and identity verification products. Lead planning, resourcing, and communication with senior leadership while ensuring the delivery of performant solutions on aggressive timelines.
Lead the design and development of computer vision and biometric systems, including face recognition and quality assessment. Own the end-to-end machine learning pipeline from data ingestion and synthetic data generation to production deployment on AWS.
Develop novel machine learning methods and contribute to the team's research agenda to improve computer vision applications. Translate research findings into scalable production systems while identifying areas for innovation.
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