Top Remote Machine Learning Engineer Jobs

As a Senior Machine Learning Engineer, you will build and productionize ML models, develop scalable infrastructure, and mentor teams to optimize marketing products.

The Senior Software Engineer I role involves developing scalable solutions, mentoring junior engineers, and collaborating on technical roadmaps within the healthcare industry.

As a Senior Machine Learning Engineer, you'll lead the development of a neural welding simulator, integrating research and production to enhance robotic systems. Responsibilities include building predictive models, collaborating with reinforcement learning engineers, and translating prototypes into maintainable production code.

Contribute to core ML infrastructure by designing, building, and optimizing training frameworks, working with research teams to implement solutions at scale.

Design and implement AI-native demand optimization algorithms and systems for auction and bidding, improving delivery efficiency and user experience.

Lead the Safety ML team as a technical lead, driving ML systems development for safety, collaborating with cross-functional teams, and tackling complex safety challenges.

The Senior Software Engineer II at Aledade will develop scalable AI/ML solutions, mentor junior engineers, and collaborate with cross-functional teams in the healthcare industry.

Lead the development of ML algorithms for robotic manipulation, focusing on multimodal perception and real-world deployment, integrating with other robotics functionalities.

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 prototype new generative models for Pinterest Canvas, oversee training data collection, mentor junior researchers, and publish findings.

Seeking a Senior Machine Learning Engineer to design and implement ML systems, optimize deployment, and collaborate with data teams, focusing on scalability and performance.

The role involves designing and operating modern data and ML platforms, building scalable pipelines, implementing MLOps systems, ensuring compliance, and enabling AI solutions in public health.

The Staff ML Platform Engineer will enhance Afresh's ML platform performance and scalability, collaborating with ML teams to improve systems and deploy models efficiently.

As a Senior Machine Learning Engineer on the Perception Team, you will define technology direction, architect solutions for autonomous vehicles, collaborate with team members, and mentor junior engineers, contributing to high-stakes projects in autonomous driving.

Design and build ML infrastructure components for autonomous vehicles, ensuring scalability and robustness for high-volume data processing and model training.

As a Senior Machine Learning Engineer, you'll build and deploy ML models for risk and fraud detection, leading technical efforts and collaborating cross-functionally.

The role involves building a recommendation engine, designing ML systems, making data-driven decisions, and collaborating with leadership to enhance user experiences.

The Senior Machine Learning Engineer will build and own production ML systems, manage end-to-end workflow, debug issues, and mentor others.

Develop and maintain machine learning solutions, collaborating on frameworks, adopting best practices, and mentoring new hires while ensuring operational excellence in production systems.

Lead and manage a new ML Acceleration team, driving strategy and development for faster ML model training and optimizing performance.

This role leads the ML Acceleration team, focusing on enhancing ML model training efficiency and team management, while driving technical strategy and collaboration.

The role involves building ML infrastructure, creating data pipelines, ensuring data quality, and collaborating with data scientists to optimize models.

The role involves building production ML models for voice AI, focusing on fine-tuning, deploying, and evaluating models to enhance human-like interactions.

The role involves deploying, optimizing, and maintaining ML-driven motion planning and control algorithms for autonomous driving, collaborating across teams to ensure reliability under performance and safety constraints.

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.