Top Senior Machine Learning Jobs in Reno, NV

As a Senior Machine Learning Engineer, you will design and deploy object detection models, collaborate with teams, and enhance ML solutions.

The role involves designing and implementing cloud-native infrastructure for AI/ML workloads, optimizing Kubernetes environments, and contributing to open-source MLOps tooling.

Lead a team of data scientists developing ML-driven products, managing infrastructure, training models, and ensuring production quality while collaborating with senior leadership.

The Machine Learning Scientist will design and evaluate algorithms for media processing, collaborate with cross-functional teams, and expand expertise in computer vision and related fields.

The Staff Software Engineer will architect, implement, and maintain foundational ML infrastructure and feature stores for Reddit, collaborating across teams to advance ML capabilities.

The role involves designing, developing, and deploying ML models, collaborating with cross-functional teams, and improving model performance through testing and experimentation.

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 Research Engineer will develop and deploy deep learning pipelines, optimize model training, and collaborate with scientists to enhance AI/ML capabilities for cancer detection.

Lead architectural vision and development of scalable infrastructure for self-driving technology, mentoring engineers and overseeing complex projects.

Develop and optimize deep learning models for trajectory generation in autonomous vehicles, focusing on planning, control, and real-time inference.

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

The Senior Solution Innovation Architect will design and implement AI/ML solutions on the Snowflake platform, collaborate with customers, and provide technical expertise in ML and AI applications.

The role involves developing advanced multimodal customer experiences using AI, mentoring others, and refining AI processes for Zillow's platforms.

The Senior Power System Studies Engineer designs and applies AI/ML techniques for power system optimization, conducts simulations, and mentors junior engineers.

The position involves driving AI/ML product development for personalized experiences, partnering across teams, and launching impactful products.

The Senior Machine Learning Consultant designs and develops machine learning solutions while mentoring team members and collaborating with clients. Responsibilities include conducting R&D on AI/ML models, optimizing model performance, and ensuring adherence to ethical AI practices.

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

The Principal Machine Learning Engineer will lead the development of AI/ML solutions to enhance user personalization within Yahoo Mail, mentor teams, and drive innovation while maintaining code quality and engineering standards.

The role involves designing, building, and managing data pipelines and machine learning solutions for veterinary care, utilizing cloud services and various programming languages while collaborating within an Agile team.

The Staff Machine Learning Engineer at Niche will lead ML initiatives, build and deploy models, measure results, mentor staff, and drive business growth through data-driven solutions.

The Senior Machine Learning Engineer will personalize user experiences, build systems for model training, collaborate with cross-functional teams, and contribute to product strategy.

The Senior Software Engineer will own large-scale data mining workflows, improve ML products through high-quality datasets, and analyze model performance across driving scenarios.

The Sr. Machine Learning Engineer will build tooling and services for ML and generative AI solutions, focusing on deployment, evaluation metrics, and cross-functional collaboration.

Lead AI and machine learning projects, create workflows and models, analyze data from diverse sources, and present insights to non-technical audiences.

Lead development of a large-scale machine learning platform, optimizing model training, data processing, and collaborating on MLOps, while ensuring scalability and performance.