Top Remote Machine Learning Engineer Jobs

Lead end-to-end design, implementation, deployment, and operation of production AI/ML-enabled full-stack applications. Build LLM-powered features, design scalable backend services and data models, deploy on Azure, implement CI/CD and observability, and mentor engineers while ensuring secure, compliant integration into clinical workflows.

As a Principal Software Engineer, you'll architect and code backend services and ML models, integrate them with Salesforce, and mentor junior engineers.

As a Staff AI/ML Engineer, you'll enhance developer productivity, mentor engineers, drive best practices, and implement scalable solutions for AV tools and services.

Lead design and development of scalable, high-performance ML training infrastructure. Drive distributed training performance optimization, observability, and developer experience. Own cross-functional infrastructure initiatives, set technical direction and standards, and mentor engineers to deliver platform capabilities that support large-scale model training.

Lead the machine learning strategy, design scalable ML systems, drive MLOps, mentor engineers, and comply with AI governance.

The Staff ML Engineer will design and operate Samsara's ML platform, collaborating with teams to enhance ML features and improve safety outcomes. Responsibilities include overseeing system reliability, leading technical direction, and mentoring engineers.

The Lead AI/ML Engineer will design and implement ML models, integrate AI solutions, and collaborate with technical teams to enhance AI capabilities, focusing on healthcare applications.

Lead end-to-end ML and perception efforts for future sensing in autonomous vehicles: design sensor architectures, multi-modal fusion, model development, metrics, simulation-driven evaluation, system integration, and production readiness while mentoring engineers and building scalable data and training infrastructure.

Develop and evaluate ML and perception models for future sensing and autonomous driving. Work on detection, tracking, classification, sensor fusion, training pipelines, validation, robustness metrics, and integrate models into onboard systems while collaborating with cross-functional teams.

Design, build, and operate production ML decision systems to detect and prevent payment fraud, account takeover, scams, and other abuse. Integrate diverse signals into low-latency serving and batch scoring, own feature pipelines and model lifecycle, develop AI-assisted triage and feedback loops, and partner cross-functionally to balance fraud reduction with legitimate customer access.

Design, build, and operate production ML systems that generate trusted signals for ranking, retrieval, recommendations, propensity/churn/LTV, and next-best-action decisioning. Define signal/data contracts, own feature and candidate generation through serving, experimentation, monitoring, and feedback loops, and evaluate long-term business impact, trust, fairness, and compliance. Partner across product, data, modeling, risk, and compliance and apply AI/agents to accelerate engineering and operations.

Design, build, and operate production ML decision systems to detect and prevent payment fraud, account takeover, identity abuse, merchant/marketplace risk, scams, and other adversarial activity. Own end-to-end production lifecycle: data contracts, low-latency inference, batch scoring, feature quality, deployment, monitoring, incident response, rollback, and feedback loops. Develop AI-assisted workflows and reusable decision capabilities while partnering with modelers, product, compliance, and operations.

Design, build, and operate production ML signal systems—ranking, retrieval, recommendations, propensity, and next-best-action—covering feature/candidate generation, serving, experimentation, monitoring, and feedback. Define signal contracts (freshness, provenance, confidence), evaluate long-term impact (trust, fairness, compliance), and partner across product, data, and risk teams to deliver reusable customer-intelligence capabilities.

Develop and deploy AI/ML models in the pharmacy domain, focusing on Generative AI technologies and collaborating with operations and capability teams.

The AI/ML Engineer will develop and deploy AI solutions using Generative AI technologies, focusing on LLMs and frameworks like LangGraph and LangChain. Responsibilities include building APIs, deploying ML models on cloud platforms, optimizing solutions, and collaborating with stakeholders.

Lead the development of automated ML-driven map reconstruction systems. Architect and implement pipelines to validate and maintain map primitives, ensuring reliability across large-scale deployments.

As a Staff Machine Learning Engineer, lead teams in designing AI solutions, managing projects, and interfacing with clients while ensuring technical excellence and operational effectiveness.

The Senior AI ML Engineer will design and implement AI/ML systems for healthcare, manage projects from ideation to release, and mentor engineers. Responsibilities include delivering quality code, driving architectural decisions, and collaborating with cross-functional teams.

The Staff Machine Learning Engineer will lead ML initiatives, partnering with multiple teams to enhance customer support through AI-driven solutions, focusing on conversational agents and research in chatbot architectures.

The role involves building user experiences, automating ML workflows, applying ML to data labeling, and collaborating across teams to improve data quality for autonomous vehicles.

The AI/ML Engineer will focus on integrating AI/ML methods into safety assurance analytics for autonomous vehicles, develop data infrastructure, and collaborate across teams to improve vehicle safety performance using large-scale data analysis.

As a Staff Machine Learning Engineer, you will design AI products on Edge devices, optimize ML model performance, and work with large-scale datasets, collaborating across teams to deliver impactful solutions.

The Staff Machine Learning Engineer will design and build scalable ML systems, mentor engineers, and drive AI strategy at SailPoint, focusing on AI-powered identity security solutions.

The Staff Machine Learning Engineer will lead ML initiatives, develop ML systems, collaborate with cross-functional teams, and mentor junior engineers to optimize healthcare intake workflows using advanced machine learning techniques.

The Machine Learning Engineer develops production ML algorithms and recommendation systems, collaborates with teams, and optimizes user experiences.