Design, train, and evaluate autoregressive and non-autoregressive speech synthesis models. Drive research on multi-modal architectures and collaborate with linguists to optimize TTS frontend behavior.
Remote Machine Learning Jobs (628)
Search = machine learning
Job category = Software Development
Set the technical direction and architecture roadmap for agentic data foundations, including memory and AI workflows. Lead cross-organizational initiatives to ship scalable, high-availability agentic systems while mentoring senior technical talent.
Staff Machine Learning Engineer, Driver Understanding and Evaluation
Waymo
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Full Time
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5 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.
Act as a player-coach leading a small team of ML scientists while contributing directly to code and model design. Take strategic ownership of specific product areas to translate ML predictions into business impact and lending outcomes.
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.
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![CI&T is hiring for remote [Job-29268] Machine Learning Engineering, Colombia](/assets/96be70cc-b65f-449c-9299-d619efa70efb.png){kind=small}
The role involves conducting exploratory data analysis and building machine learning models for demand forecasting and resource optimization in the public transportation industry. Responsibilities include developing data pipelines, creating operational dashboards, and collaborating with stakeholders to translate business rules into technical features.
Develop and maintain end-to-end Machine Learning pipelines, including training, validation, and deployment. Manage the model lifecycle, monitor performance for data drift, and expose models via scalable APIs.
Lead the Conversation Memory team in developing 0-to-1 platform features for context-aware conversational AI. Act as a player-coach to bridge theoretical research with production-grade deployment while managing a team of ML engineers.
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, train, and improve cutting-edge large-scale machine learning models and deployment pipelines. Collaborate with product teams to develop safer, faster, and more efficient AI solutions.
Design, train, and deploy machine learning models at the edge to detect anomalies and block sophisticated cyber attacks in real time. Build robust data pipelines to automate defense mechanisms and monitor model performance against evolving threats.
Lead the people management, growth, and performance of the Machine Learning team focusing on the Rosso AI engine. Establish operating rhythms, hiring pipelines, and collaboration frameworks between ML and software engineering teams.
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
·
5 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
·
5 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.
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.
Lead the strategy and execution for machine learning within the ads and offers optimization domain to drive user engagement and business growth. Manage teams responsible for ads infrastructure, ranking, and personalization while aligning technical investments with business outcomes.
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Define the technical strategy and architecture for ML systems powering data discovery and model improvement lifecycles. Lead cross-functional initiatives to build scalable frameworks for multimodal data mining and optimized production inference.
Define the technical strategy and architecture for ML systems powering data discovery and model improvement for autonomous vehicles. Lead cross-functional initiatives and mentor engineers to ensure scalable, high-performance production inference.
Define the technical strategy and architecture for ML-powered data mining systems to improve autonomous driving stacks. Lead cross-functional initiatives, mentor engineers, and establish department-wide standards for ML system design and deployment.
Define the technical strategy and architecture for ML systems powering data discovery and model improvement for autonomous vehicles. Lead cross-functional initiatives and mentor engineers to ensure scalable, high-performance production inference.
Principal Machine Learning
AAA Life Insurance Company
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Full Time
·
5 Weeks Ago
AAA Life Insurance Company
Lead the technical strategy and architecture for production-grade AI and agentic systems across enterprise initiatives. Drive the development of autonomous AI agents to improve operational efficiency in Claims, Underwriting, and Member Services.
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.
Develop and deploy machine learning and computer vision systems for real-world applications, focusing on OCR and license plate recognition. Design CNN-based models and integrate them into production software pipelines for edge and cloud infrastructure.
Machine Learning Engineer I, Personalization , Minesweeper
Spotify
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Full Time
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5 Weeks Ago
Spotify
Develop and refine Spotify's content enrichment and recommendation systems using LLMs and ML techniques. Collaborate with cross-functional teams to build scalable systems for understanding music, podcasts, and audiobooks.
Own the full lifecycle of ML model development, focusing on forecasting and predictive modeling for grid capacity. Collaborate cross-functionally to translate business objectives into production-grade data analytics and operational workflows.
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Senior Machine Learning Infrastructure Engineer
Unity Technologies
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Full Time
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6 Weeks Ago
Unity Technologies
Design and maintain scalable infrastructure for serving machine learning models in real-time within a high-scale advertising ecosystem. Partner with ML engineers to productionize models and optimize latency, throughput, and reliability.
Senior Machine Learning Infrastructure Engineer
Unity Technologies
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Full Time
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6 Weeks Ago
Unity Technologies
Design and maintain scalable infrastructure for serving machine learning models in real-time within a high-QPS advertising ecosystem. Collaborate with ML engineers to productionize models and optimize inference performance, latency, and cost-efficiency.
Senior Machine Learning Infrastructure Engineer
Unity Technologies
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Full Time
·
6 Weeks Ago
Unity Technologies
Design and maintain scalable infrastructure for serving machine learning models in real-time within a high-scale advertising ecosystem. Partner with ML engineers to productionize models and optimize inference performance, latency, and cost-efficiency.
Develop novel machine learning algorithms for applications in energy, healthcare, and robotics. Create software simulations and prototype systems to analyze and prove the performance and practicality of these algorithms.
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