Top Senior Machine Learning Jobs in San Diego, CA

As a Senior Software Engineer in Machine Learning, you'll develop and maintain machine learning models for geospatial analytics, collaborate with teams to refine algorithms, and ensure high-quality deployment of models at scale.

The Staff Machine Learning Engineer will develop and maintain MLOps tools, optimize model performance, and collaborate on ML system architecture with a focus on enhancing developer experience.

Develop and tune ML models, productionize and deploy strategies for ML systems, and align cross-functionally to communicate performance metrics.

The Senior ML Engineer will design evaluations for AI features, optimize pipelines, and ensure quality in ML systems while collaborating with cross-functional teams.

Collaborate to scale self-driving systems, build training frameworks, profile model performance, and evaluate emerging technologies for training and inference.

Lead the design and deployment of scalable ML infrastructure, focusing on MLOps and LLM strategies, while mentoring team members and ensuring operational maturity.

The Staff Machine Learning Engineer will enhance Quora's recommendation systems, lead machine learning projects, and own end-to-end ML processes.

As a Staff Software Engineer, you'll develop and maintain backend and pipeline systems for search and recommendation services on Reddit, focusing on low-latency, scalable model-serving APIs.

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

Implement and optimize production-ready analytics code, maintain Python repositories, research data sources, build predictive models, and collaborate with teams.

Lead product marketing initiatives at Viaduct, creating compelling content, partnering with sales and product teams, and driving demand in the automotive sector.

As a Principal ML Architect, lead technical strategy and client engagements, mentor ML engineers, and oversee project lifecycle in delivering complex AI systems.

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

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

As a Senior ML/AI Platform Engineer, you will design and productionize scalable AI/ML models, mentor junior engineers, and collaborate with cross-functional teams to optimize machine learning pipelines.

The Lead Machine Learning Scientist designs and develops ML solutions, leads project teams, mentors members, and collaborates with clients to solve complex problems.

As a Staff Machine Learning Engineer, you will design scalable ML systems, mentor engineers, solve complex problems, and optimize models in a fintech environment.

As a Machine Learning Engineer, you'll develop datasets and pipelines for navigation applications, work with geospatial data, build ML models, and ensure data quality.

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

As a Principal Solutions Architect, you will architect AI/ML solutions, lead teams, engage clients, and drive account growth while ensuring delivery excellence.

The role involves designing, optimizing, and deploying large-scale ML/AI automation systems, ensuring service availability and cost efficiency through architectural best practices.

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

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