Top Remote Machine Learning Jobs

The Senior Applied Scientist II is responsible for designing and implementing ML models to optimize the supply chain, collaborating across teams, and driving data-driven decision-making.

The Senior Machine Learning Engineer will develop ML APIs, build data pipelines, and collaborate across teams to enhance ML models and applications.

As a Senior Machine Learning Engineer, you will design ML infrastructure, lead zero-to-one initiatives, collaborate on projects, and enhance scalability in the development of ML applications.

The role involves building AI technologies for customer service, developing ML systems, and collaborating with cross-functional teams to enhance user experiences.

The Senior Machine Learning Engineer will design, prototype, build AI systems, evaluate ML models, and improve Vectara's AI Agents with a focus on reliability and performance.

Develop and maintain predictive models for quality, risk adjustment, and operational efficiency; analyze multi-source healthcare data; implement ML solutions, monitor model performance, and experiment with emerging AI to improve outcomes and workflows.

Lead the design and delivery of large-scale machine learning systems, mentoring engineers while driving technical strategy and collaboration across teams in AEC solutions.

Design and improve end-to-end ML/AI pipelines, process datasets, and contribute production code for high-quality solutions in machine learning projects.

As a Staff Machine Learning Engineer, you will design and implement infrastructure for AI workloads, collaborate on GPU cluster performance, and write scalable code while mentoring colleagues.

Lead the ML and AI engineering team, strategizing and implementing AI solutions for business growth, mentoring staff, and collaborating across departments.

Design and implement knowledge distillation pipelines, optimize training and inference performance, and collaborate with research on production-ready ML models.

Design, develop, and maintain algorithms for engineering applications, manage datasets, and implement machine learning workflows in an AI Copilot startup.

The Senior Machine Learning Engineer will develop core ML models, manage data pipelines, and collaborate with stakeholders to deliver scalable ML solutions.

Develop and optimize machine learning models and workflows to enhance insurance processes. Collaborate on model integration, monitoring, and improvement while driving innovation in modeling techniques.

The role involves building ML systems, improving models across product surfaces, and leveraging data for personalization and user engagement.

The Principal Software Engineer II will build and maintain machine learning components in Elasticsearch, collaborating with teams, writing scalable code, and owning projects from design to implementation.

Lead end-to-end AI/ML projects: research, prototype, optimize, and productionize ML and LLM solutions for healthcare. Mentor and recruit teams, run experiments and A/B tests, present results to leadership, and pursue AI research and IP.

Develop and evaluate novel AI/ML solutions for healthcare using structured and unstructured data. Build deep learning and classical ML models, design experiments, analyze results, document models, collaborate on MLOps pipelines, and ensure responsible AI compliance with stakeholders.

Lead AI/ML engineering to design, build, and deploy predictive models and reusable ML platforms. Mentor scientists and engineers, collaborate cross-functionally, ensure responsible AI compliance, and publish or patent novel methods. Drive adoption of GenAI/LLM solutions and production-grade pipelines for healthcare use cases.

Lead development of AI/ML solutions for healthcare using structured and unstructured data. Build and test deep learning and classical ML models, design experiments, perform statistical analysis and visualizations, ensure responsible AI compliance, produce documentation/patents/publications, and collaborate on MLOps pipelines and stakeholder integrations.

Design, develop, and deploy production-grade AI/ML models and pipelines (LLMs, RAG, Transformers). Work with agentic frameworks, scale training/inference on Databricks/PySpark, integrate solutions via Docker and REST APIs, leverage cloud services (Azure/AWS), participate in AI governance, and mentor junior engineers to deliver measurable pharmacy optimization outcomes.

Build and optimize machine learning models for 3D dental applications, research state-of-the-art methods, and implement MLOps best practices.

Lead the design, development, and deployment of machine learning models, collaborating with teams and mentoring engineers. Focus on scalable ML workflows.

The Principal ML Engineer at Agero will develop and productionize a Dispatch System using ML models, optimize decision-making processes, and lead a team to improve operational performance.

As a Senior Machine Learning Engineer, you will design and implement systems for ML and NLP, optimizing models and tools for Clover's healthcare solutions.