Top Machine Learning Jobs in San Diego, CA

Lead AI initiatives and governance, enhance AI capabilities, and develop internal training programs while collaborating across teams.

The AI Engagement Manager will foster relationships with top partners, facilitate adoption of AI solutions, and analyze performance using BI tools.

The Sr. Product Designer will create user-centered mobile experiences for AI-supported mental health therapy. Responsibilities include designing workflows, collaborating with teams, and utilizing strong design skills in mobile applications.

As a Machine Learning Engineer, you'll enhance ML productivity, improve model deployment, and implement algorithms for credit decisioning systems.

Lead the Security & Risk department, overseeing cybersecurity and fraud prevention while implementing security automation and tools for innovation. Manage a skilled team, foster partnerships, and ensure physical security for employees and operations.

As an Account Executive, you'll drive strategic sales, acquire new enterprise customers, negotiate contracts, and manage a sales pipeline for Runpod's AI infrastructure offerings.

The Signal Processing Engineer will perform data analysis, develop algorithms, support software implementation, and participate in maritime defense tests, necessitating a strong background in signal processing and AI/ML.

As a Director of Financial Risk Management, you will oversee risk analytics, lead AI initiatives, manage risk frameworks, and ensure regulatory compliance while mentoring teams and collaborating across departments.

Lead the development of Computer Vision and Machine Learning projects at Dandy, focusing on 3D geometric problems and automation in dental manufacturing.

Join Tecton as a Solutions Architect to drive technical decisions, enable customer adoption of AI/ML solutions, and provide expertise in data systems.

The Vice President of Software Engineering oversees all technology operations, leads the engineering team, creates technology strategies, and ensures alignment with organizational goals. Responsibilities include evaluating technology opportunities, enhancing customer experience, and managing IT initiatives within budget and timelines.

This internship focuses on applying AI and predictive sciences in genomics. The intern will work on data curation, tool development, and communication of findings.

This role leads the development of machine learning platforms, overseeing teams to deliver scalable data solutions and recommendation systems for consumer marketplaces, aligning with business goals.

Lead and mentor a team of fraud analysts to identify and mitigate fraudulent activity. Collaborate with cross-functional teams to improve fraud detection processes and develop ML models for risk management.

As a Software Engineer at Upstart, you will develop scalable APIs for data retrieval and decisioning while collaborating with teams to enhance ML models' performance, ensuring data quality and reliability through testing.

As a Senior Data Scientist, you will analyze data, build models, and collaborate with teams to enhance credit evaluation using machine learning.

The Senior Machine Learning Engineer will evaluate and apply advanced ML models, integrate with company infrastructure, and support data pipeline orchestration while focusing on autonomous vehicle technology.

As a Machine Learning Security Researcher, you will conduct research on security for machine learning systems, develop security frameworks, and engage with AI organizations to assess and improve their security posture.

Lead centralized Machine Learning efforts at Affirm, managing model development lifecycles, fostering AI adoption, and overseeing a team of ML professionals to enhance business outcomes.

The Senior Data Scientist will optimize product performance, drive product innovation through data-driven insights, and foster a culture of data-driven decision-making across teams.

The Senior Engineer in Photonic Design & Testing will design, develop, and test advanced photonic systems and algorithms, while collaborating with various engineering teams to enhance sensor capabilities.

Lead a team of ML and DevOps engineers to build infrastructure for the ML ecosystem, including tools for experimentation and deployment. Manage a distributed team while enhancing capabilities in ML system operation and analytics production.

Lead the design and implementation of AI-driven forecasting and financial modeling systems, collaborating across teams to enhance decision-making and operational reliability.

The Machine Learning Modeler will design and scale intelligent systems for data-driven decision-making, implementing ML pipelines, and collaborating with analytics teams for model production and insights.

Design and build a machine learning platform, deploy ML models, collaborate across teams, and establish monitoring standards for AI solutions.