Develop and maintain AI systems to automate customer operations such as disputes, returns, and fraud handling. Build LLM-powered pipelines for evidence extraction and prototype new modeling approaches to drive production improvements.
Remote Machine Learning Engineer Jobs (516)
Search = Machine Learning Engineer
Principal Machine Learning Engineer- LLM Fine-tuning and Optimization
Airbnb
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Full Time
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7 Weeks Ago
Airbnb
Responsible for fine-tuning and optimizing state-of-the-art LLMs for diverse use cases and high-performance deployment on Airbnb's ML infrastructure. You will design AI products like AI Assistants and autonomous agents while creating a multi-year technical roadmap.
Architect and code high-performance backend services and ML pipelines to automate sales operations and lead prioritization. Build 0-to-1 internal tools leveraging LLMs and Agentic AI to integrate custom quoting software with Salesforce.
Senior Machine Learning Engineer, AI Generation Engine
SandboxAQ
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Full Time
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7 Weeks Ago
SandboxAQ
Design and manage robust data pipelines and develop novel ML models for Large Quantitative Models and agentic frameworks. Collaborate with cross-functional teams to translate business objectives into actionable ML development and production roadmaps.
Design, build, and operate AI-powered features and products to create magical experiences for Calendly customers. Collaborate with cross-functional teams to implement AI solutions and manage the end-to-end lifecycle of ML services and data pipelines.
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Sr. Staff Machine Learning Engineer, Content Ecosystem
Pinterest
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Full Time
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7 Weeks Ago
Pinterest
Lead the technical strategy for ML systems to improve Pinterest's content ecosystem, focusing on supply, distribution, and long-term ecosystem health. Design multi-objective optimization approaches to balance relevance, quality, and monetization while mentoring junior engineers.
Lead the technical vision and development of state-of-the-art applied ML projects for ads conversion. Design large-scale DNN models and mentor engineers while collaborating with product and sales teams.
Senior Machine Learning Engineer, Vector Bidding Science
Unity Technologies
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Full Time
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7 Weeks Ago
Unity Technologies
Design and optimize core bidding algorithms and auction mechanisms to maximize advertiser returns. Architect scalable bid landscape forecasting and analyze marketplace dynamics to drive algorithmic improvements.
Serve as the technical lead for an ML team focusing on personalization, relevance, and ranking. Own the end-to-end architecture, from model training and evaluation to deployment and scaling in production.
Design, build, and deploy high-quality machine learning models and scalable pipelines to detect security threats and sensitive data. Collaborate with cross-functional teams to align ML initiatives with business goals and mentor other engineers.
Design and implement custom GPU/accelerator kernels to maximize performance for next-generation AI workloads. Collaborate with researchers to translate algorithmic advances into efficient, production-ready code.
Develop pipelines for post-training tasks including fine-tuning, evaluation, and model compression. Implement scalable systems for model deployment and optimization while collaborating with researchers to validate results in production.
Machine Learning Engineer III - FES
Fanatics Betting & Gaming
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Full Time
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8 Weeks Ago
Fanatics Betting & Gaming
Own the end-to-end ML infrastructure for recommendation, personalization, and LTV scoring systems. Build and scale real-time and batch feature pipelines and model serving infrastructure across the Fanatics ecosystem.
Lead the development and deployment of end-to-end AI, ML, and Agentic AI solutions for cloud cost optimization and workload management. Collaborate cross-functionally to translate business requirements into a technical ML roadmap and champion MLOps best practices.
Lead the development and deployment of end-to-end AI, ML, and Agentic AI solutions within a cloud-native environment. Drive strategic initiatives for intelligent workload management, cloud cost optimization, and MLOps best practices.
Senior Machine Learning Engineer (RecSys)
INFOMEDIJI d.o.o.
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Full Time
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8 Weeks Ago
INFOMEDIJI d.o.o.
Design and build real-time ranking and retrieval models for video recommendations, search, and infinite scroll timelines. Develop end-to-end ML pipelines and explore algorithms for short-form video generation.
Own the end-to-end ML/AI lifecycle from defining success metrics and prototyping to deploying production-ready models. Collaborate with engineering and product teams to automate complex tax and accounting workflows using LLMs and traditional ML.
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Design and implement machine learning models, algorithms, and full-stack API services for AI-driven products like Dayforce AI Assistant. Manage end-to-end ML pipelines from data preprocessing and training to production deployment and monitoring.
Design and implement machine learning models, algorithms, and full-stack API services for AI-driven products like Dayforce AI Assistant. Manage end-to-end ML pipelines from data preprocessing and training to production deployment and monitoring.
Build and operate production AI pipelines and Airflow-based orchestration for clinical workflows. Develop observability and evaluation infrastructure to ensure the quality and reliability of LLM outputs in healthcare applications.
Staff Machine Learning Engineer, Driver Understanding and Evaluation
Waymo
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Full Time
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8 Weeks Ago
Waymo
Lead the development of cutting-edge deep learning and Gen AI models to analyze autonomous vehicle behavior and automate high-volume workflows. Collaborate with cross-functional teams to define technical strategy and optimize ML models for fleet-wide evaluation.
Design and run experiments to improve AI agent quality, reasoning, and tool use within the Breeze Studio platform. Build evaluation infrastructure and optimize LLM inference for latency, cost, and quality tradeoffs.
Design, build, and operate production-grade machine learning systems to transform rich media and spatial signals into immersive customer experiences. Lead end-to-end ML workflows from prototyping and training to deployment and observability in production.
Design and implement knowledge graph architectures using Neo4j or RDF models to drive AI product development. Integrate these graphs with LLMs using RAG architectures and build robust APIs for network traversal and relationship analysis.
Staff Machine Learning Engineer, Credit Products (Square Financial Services)
Block
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Full Time
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9 Weeks Ago
Block
Lead the design and implementation of the full credit modeling stack to drive growth for Square Financial Services. This includes managing the entire lifecycle of credit decisioning and scaling ML infrastructure within a regulated banking environment.
Staff Machine Learning Engineer, Credit Products (Square Financial Services)
Block
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Full Time
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9 Weeks Ago
Block
Lead the design and implementation of the full credit modeling stack to enhance predictive accuracy for underwriting. Manage the entire lifecycle of credit decisioning, from data ingestion to production integration within a regulated banking environment.
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The Machine Learning Engineer will build and integrate machine learning solutions into defense capabilities, focusing on real-time data processing. They will lead the development of feature detection and anomaly detection models and collaborate with cross-functional teams.
Design, develop, and deploy end-to-end machine learning pipelines and MLOps best practices. Optimize models and collaborate with data engineers to build scalable, production-ready inference systems.
Design, train, and deploy classical ML and generative AI solutions using a cloud-native AWS stack. Collaborate with product managers to translate business needs into scalable AI components across healthcare business units.
Design and implement scalable AI systems and agentic applications using LLMs, RAG, and tool calling. Monitor production performance and provide technical leadership for infrastructure and architectural improvements.
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