Top Machine Learning Engineer Jobs

The role involves developing and optimizing tokenization systems for machine learning, collaborating with research teams, and improving model training efficiency.

Develop applications for machine learning and generative AI technologies, automate data analysis, and collaborate on prototyping solutions for semiconductor testing.

The role involves building and improving systems for training AI models, focusing on algorithms and infrastructure for reinforcement learning. Responsibilities include enhancing performance, reliability, and usability of systems to support research.

The role involves designing and maintaining machine learning models, analyzing data, and optimizing algorithms to solve business problems.

Design and implement machine learning models to solve business problems, analyze data for insights, and optimize model performance.

Design, build, and deploy ML infrastructure components for autonomous vehicles, focusing on model training pipelines and optimizations.

The role involves optimizing machine learning models, developing infrastructure for model life cycles, and collaborating across teams to enhance Nuro's autonomy technology.

Develop and optimize 3D graphics algorithms for sensor simulation, leveraging GenAI/ML techniques. Collaborate with various teams to enhance simulation realism and generate high fidelity data.

Develop and optimize 3D rendering algorithms for sensor simulation using cutting-edge graphics and GenAI/ML techniques, collaborating with various teams to enhance data fidelity.

As a Senior Machine Learning Engineer on the Perception Mapping team, you'll develop ML models for semantic map detection, integrate them into autonomy systems, and lead technical efforts in model validation and best practices.

Design and develop innovative features for Mirage, managing key software ownership, collaborating with teams to build scalable back-end systems and APIs.

As a Senior Research Engineer, you will optimize language and vision models on Cerebras hardware, focusing on high-performance ML inference techniques.

Develop ML-first behavior modules for predicting future motions of road users. Collaborate with perception and planning teams to enhance autonomous systems.

Design and implement distributed cloud GPU training for ML, build end-to-end pipelines, collaborate on data problems, and uphold ML best practices.

Lead software engineer focusing on optimizing ML models for embedded systems, improving performance and efficiency in production environments.

The ML Perception Software Engineer will develop perception modules for autonomous vehicles, focusing on machine learning and computer vision to enhance navigation capabilities.

Develop and apply deep learning and data analysis techniques to create scalable vehicle simulation models, collaborating with teams to advance autonomous technology.

Design and deploy machine learning models for autonomous vehicles, focusing on data tagging, dataset curation, and model validation.

Conduct applied research in robotics and develop ML pipelines for training models on data collected by Scale, collaborating with customers and cross-functional teams.

The Data Engineer will build data infrastructure for AI applications, design ETL pipelines, collaborate on ML model support, and ensure data governance.

The Full Stack Software Engineer will design, build, and deploy web applications that integrate AI and ML capabilities, developing tools and APIs to enhance consumer experiences.

Lead the design, development, and implementation of machine learning products, creating data pipelines and maintaining production stability.

As a Senior Machine Learning Engineer at Haystack News, you'll build models for user engagement, enhance algorithms, and work on cross-functional teams to deliver data-driven insights.

Develop algorithms for robotic intelligence, including vision-language models and multi-modal data integration for human-robot communication.

In this role, you'll collaborate on AI and machine learning projects, develop solutions, tune neural networks, and maintain code stability.