Top Remote Machine Learning Jobs in San Diego, CA

Drive delivery excellence and customer success by leading the architecture and implementation of AI/ML solutions while ensuring account growth and client engagement.

As a Research Intern, you will work on AI/ML projects, contributing to the development of the Nebula LLM and applying machine learning techniques to real-world problems.

As a ML Engineer focused on inference, you'll design and optimize deep learning models for real-time communication AI applications, collaborating with cross-functional teams and ensuring production readiness.

Design and maintain scalable machine learning infrastructure, collaborating with data scientists, ensuring performance, security, and compliance of AI systems.

The ML Engineering Intern will contribute to the Nebula LLM development, tackle machine learning challenges, and gain hands-on experience in AI and language technology.

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.

Lead definition and implementation of the companys ML strategy and infrastructure. Build end-to-end production ML systems (data pipelines, training, evaluation, serving), own data strategy and feedback loops, integrate ML with product/backend, write production-quality code, and recruit/mentor the ML team as it scales.

As an AI/ML Ops Engineer, you will architect and operate ML pipelines, automate CI/CD processes, and collaborate with cross-functional teams to enhance engineering productivity.

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.

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.

Design, architect, and deploy generative AI/LLM solutions from prototype to production; work directly with clients to translate business needs into technical plans; write production-quality code integrating LLMs and ML models; collaborate with cloud, DevOps, and frontend teams; support proposals, sales, and evaluation/observability of models.

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

Intern will collaborate with data scientists and ML engineers to develop machine learning models and improve data pipelines for retail media insights.

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 Senior AI/ML Data Product Owner will drive the development of AI/ML solutions, manage the project backlog, and align business and technical teams to ensure effective execution of data-driven projects.

The Director of Machine Learning Science will lead teams in delivering ML solutions, drive innovation in search and personalization, and engage with engineering and product teams.

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 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.

As a Staff Machine Learning Engineer, optimize card pricing models, lead ML lifecycle, collaborate with experts, and enhance predictive features.

The Machine Learning Engineer will design and deploy computer vision models, build training pipelines, and enhance ML infrastructure to improve agricultural field operations.

The Senior Machine Learning Engineer will drive innovation by building and operating AI-powered features for Calendly's clients, focusing on high-quality design and deployment processes.

The role involves designing and supporting GPU/Kubernetes clusters for AI/ML workloads, developing automation tools, and troubleshooting infrastructure issues.

As an AI/Machine Learning Intern, you will contribute to software applications and AI projects, working with data engineers and researchers to implement innovative solutions.

The intern will work on AI projects, gaining hands-on experience in software development, algorithm evaluation, and collaboration with engineers to enhance AI capabilities.

As a Senior Technical Recruiter for AI/ML, you'll manage full-cycle recruiting for senior AI roles, build talent pipelines, and partner with leadership to close top talent effectively.