AI Engineer | Python | AI Agents | Chatbots | Machine Learning | Full Stack | Remote
Develop and deploy machine learning models and build backend systems using Python. Integrate AI solutions with full-stack applications and develop REST APIs.
Remote Machine Learning Jobs (639)
Machine Learning Engineer
Design and optimize machine learning models for medical image analysis to improve prostate cancer diagnosis and treatment. Build scalable data pipelines and integrate AI models into clinical software solutions while ensuring regulatory compliance.
Principal Machine Learning Architect
Design and implement complex data-centric ML solutions, including feature generation and model delivery systems. Manage the deployment, hosting, and monitoring of ML models to optimize large-scale ad tech data.
Senior Machine Learning Engineer (RecSys)
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.
Senior Data Scientist + Machine Learning Engineer
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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VA
Staff Data Scientist, Machine Learning in Epidemiology and Patient Data Products
Lead the development of machine learning methods and analyses of high-dimensional longitudinal patient data to generate clinical insights. Collaborate with cross-functional teams to build and operationalize ML pipelines within a computational platform for drug discovery.
Machine Learning Scientist
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.
Senior Manager, Machine Learning
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.
Machine Learning Intern/Co-op (Fall, 2026)
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.
Machine Learning Engineer, Underwriting
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.
CA
Machine Learning Software Engineer
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.
Senior Machine Learning Infrastructure Engineer
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
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
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.
Senior Machine Learning Engineer (Agentic AI)
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.
Machine Learning Scientist 5, Markeplace - Ads DSE
Design and implement machine learning and optimization algorithms to enhance ad quality, performance, and yield within the ad marketplace. Collaborate with product teams to define business objectives and communicate technical results to stakeholders.
Machine Learning Lead (LLM)
Lead a team of senior data scientists in developing ML-driven products, focusing on fine-tuning LLMs and building production inference systems. Collaborate with leadership to define the technical roadmap and translate model outputs into actionable strategic insights.
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Sr. Machine Learning Engineer
Design and deploy ML models for document classification, entity extraction, and summarization of complex financial documents. Build scalable production-ready ML services and contribute to the MLOps stack including CI/CD and evaluation frameworks.
Senior Machine Learning Developer, Advertiser Growth
Architect GenAI systems for creative asset generation and design sophisticated budget pacing algorithms to manage advertiser spend. Build high-scale billing pipelines and experimentation infrastructure to optimize marketplace ROI and financial integrity.
Machine Learning Engineer
Define model development methodologies and best practices while managing the full ML lifecycle. Develop tools and pipelines to support the productionalization of ML-driven microservices.
Senior Machine Learning Engineer (RecSys)
Design and implement retrieval and ranking architectures for personalized music recommendations. Build end-to-end ML systems encompassing data processing, training, deployment, and performance monitoring.
Machine Learning Software Engineer II
Lead the transition of machine learning models from research prototypes into scalable, high-performance production systems on AWS. Design and deploy custom ML solutions while optimizing inference throughput and latency using tools like ONNX and Flash Attention.
Tech Lead Manager (Machine Learning) |M1|
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.
Member of Technical Staff, Machine Learning
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.
Senior Machine Learning Engineer
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.
Principal Machine Learning Engineer
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.
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Senior Machine Learning Engineer
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.
Machine Learning Engineer 5 - Globalization
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.
Mid-Level Machine Learning Engineer
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.
Senior Machine Learning Engineer
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.
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