Top Remote Machine Learning Jobs

As a Machine Learning Subject Matter Expert, analyze ML systems, validate claims, evaluate model performance, and collaborate with teams to report findings.

The Engineering Manager, Machine Learning will lead a team focusing on 3D deep learning and computer vision, manage the ML roadmap, and implement best practices for MLOps pipelines.

Lead end-to-end machine learning solutions for autonomous driving, mentor engineers, design advanced models, and ensure safety and reliability in diverse scenarios.

As Engineering Manager, you'll lead a team of engineers to develop data products, enhance host engagement, and inform pricing strategies through analytics and machine learning.

The Staff Machine Learning Engineer designs and implements infrastructure for AI workloads, collaborates with teams, mentors, and ensures code quality, focusing on machine learning and distributed systems.

Develop and deploy machine learning solutions for autonomous driving, collaborating with cross-functional teams and mentoring engineers for technical excellence.

Lead and develop advanced machine learning models for autonomous driving, collaborating with teams, and driving technical initiatives in a hybrid work environment.

The Machine Learning Engineer will work on unstructured data classification and clustering, utilizing their expertise in AI systems and various programming languages.

The Senior Machine Learning Engineer will utilize deep experience and insights to enhance communication and digital interactions through advanced machine learning tools and algorithms, focusing on unstructured data.

Lead development and production deployment of advanced ML and time-series models for water and infrastructure systems, perform research in Physical AI, collaborate cross-functionally, communicate impact to stakeholders, and mentor junior data scientists.

Lead research on machine learning validation for robotics and autonomy systems, focusing on simulation, uncertainty modeling, and creating functional prototypes for testing.

Lead the design and development of real-time machine learning personalization architecture, focusing on user experience and dynamic content discovery.

Develop scalable machine learning services for data enrichment, managing the ML lifecycle from model training to deployment, and ensuring performance and reliability standards.

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 Senior Applied AI/ML Scientist will lead the design and deployment of AI solutions, collaborate on impactful features, and enhance product capabilities by leveraging advanced AI and ML techniques.

The Director of Machine Learning Engineering is responsible for leading AI strategy, overseeing ML solutions, driving innovation, building teams, and ensuring operational excellence in ML systems.

The role involves designing and implementing scalable ML-based solutions, analyzing data patterns, and producing reports while staying updated on AI advancements.

Lead the development of production-grade machine learning systems, build ML pipelines, and optimize models for deployment and performance.

Lead and build a Machine Learning team, driving strategy and execution across product areas like Document Generation and Voice Agents while collaborating with Product and Engineering.

As a Machine Learning Engineer, you'll design AI/ML solutions, optimize pipelines, integrate models, and enhance AI capabilities while collaborating with teams.

Design, build, and deploy AI features for claim synthesis; implement machine learning solutions and improve model performance through collaboration and evaluation.

As a Machine Learning Engineer at Cisco ThousandEyes, you will develop, evaluate, and implement AI/ML models, including Deep Learning and Large Language Models, and manage large-scale ML pipelines.

Lead machine learning initiatives to enhance underwriting model accuracy. Design and implement advanced training strategies and optimize workflows. Mentor engineers and influence modeling strategy.