Top Remote Machine Learning Jobs in San Diego, CA

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

You will build and own end-to-end ML systems, focusing on training, evaluation, deployment, and integration with applications, while ensuring quality and efficiency.

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

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 at ZoomInfo, you will enhance core datasets through ML/NLP solutions, manage entity resolution tasks, and drive cross-functional impact by mentoring teams and collaborating on ML KPIs.

Senior AI/ML Engineer responsible for designing, building, and deploying AI/ML systems, mentoring teams, and leading cross-functional collaborations to drive AI solutions.

The Staff Software Engineer will build and scale machine learning systems for personalization, collaborating with teams to enhance project quality and performance.

Define ML strategy and build production ML systems end-to-end (data pipelines, training, evaluation, inference). Own data strategy, integrate ML with product/backend, write production-quality code, and recruit and mentor the ML team while setting technical direction.

As a Machine Learning Engineer at Shipwell, you'll build and scale AI-powered logistics solutions, maintaining data pipelines and ML infrastructure across the organization.

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

Design and develop AI capabilities and scalable microservices. Collaborate to integrate AI models and ensure performance in cloud environments.

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

Manage a team of data scientists to develop fraud detection models, lead planning and collaboration with leadership, and communicate outcomes effectively while maintaining strong business intuition and technical leadership.

Lead technical strategy and architecture for machine learning systems, mentor engineers, and design scalable solutions for data mining and real-time inference.

The Director of Data Engineering, ML & AI leads data strategy and AI capabilities, managing a team to enhance data infrastructure, machine learning systems, and sustainability analytics while driving company-wide AI initiatives.

The Solutions Engineer will drive the adoption of AI-powered solutions in the electric utility sector, providing technical consulting and customer enablement. Responsibilities include gathering requirements, architecting solutions, leading RFI/RFP processes, and delivering training. Extensive travel is required for client engagement.

Senior ML research leader who translates state-of-the-art ML pipeline insights into product requirements, reference architectures, benchmarks, and platform roadmaps. Partners cross-functionally and with strategic customers and research institutions to set evaluation standards, reproducibility, and responsible ML practices while providing technical leadership and influencing product and executive audiences.

As a Software Engineer in ML Infrastructure, you will develop scalable data pipelines, enhance data discovery, and collaborate with teams on data organization and ML features.

The Machine Learning Engineer will develop and maintain scalable ML systems, collaborate across teams, and innovate solutions for real-time applications to enhance customer experiences.

The Senior Machine Learning Engineer at Grailed will enhance personalization and recommendations, develop AI/ML solutions, and collaborate across departments for data-driven insights.

Lead the development and deployment of ML models to optimize pricing and enhance customer experiences. Drive AI strategies, conduct research, and collaborate across teams.

Develop AI-powered solutions for personalized content and marketing. Collaborate with teams to optimize ML models and pipelines at scale, mentoring engineers and driving strategic growth initiatives.

Serve as the presales technical expert for ML capabilities: lead discovery, architect ML solutions, run demos/workshops/proofs-of-concept, coordinate cross-functional teams, and inform product direction based on customer feedback.

The Machine Learning Engineer will develop and enhance search and retrieval systems, adapting search behaviors and integrating ML models for product recommendations, while managing infrastructure and data processing.

As a Machine Learning Engineer, you will own the full lifecycle of ML from model development to production deployment, collaborating with teams to drive ML processes.