Machine Learning Jobs in Irvine, CA

Lead AI engineering teams to design, build, and deploy end-to-end AI solutions. Manage client relationships, plan and deliver projects, mentor staff, drive adoption of cloud-native microservices, CI/CD, vector databases and orchestration tools, and ensure high standards of quality, innovation, and compliance.

Support the Chief Product Officer to develop product strategy, governance, and roadmap execution. Build planning processes, drive go-to-market strategies, coordinate cross-functional teams, analyze product performance and customer feedback, and integrate product plans with enterprise systems to launch and scale space-related products.

The Sr Engineer will develop AI/ML models for health monitoring devices, focusing on algorithm development, data analysis, and cross-functional collaboration.

Drive the full enterprise sales cycle for Microsoft-based solutions in manufacturing. Develop account and territory plans, co-sell with Microsoft, engage C-level stakeholders, manage forecasts, and collaborate with internal specialists to close opportunities.

Drive pricing strategy by analyzing market and internal data to maximize revenue and profit. Build and run statistical and pricing models, extract and preprocess data from multiple sources, synthesize findings, and present recommendations to stakeholders. Work cross-functionally with Sales, Finance, Product, and project managers to implement pricing opportunities and improvements.

Lead architecture and implementation of production-grade agentic systems integrating LLMs across applications. Drive LLM integration strategy, cognitive automation roadmap, scalable distributed system design, best practices, cross-functional alignment, and mentor engineering talent.

Lead discovery product efforts across search, browse, and live feed to help viewers find and connect with creators. Define recommendation requirements, partner with ML, design, and engineering, run experiments, measure impact, and own the discovery roadmap to improve ranking, relevance, and viewer retention.

Lead process assessments and improvement across mortgage operations. Map workflows, identify automation and training gaps, manage vendors, conduct UAT, surface regulatory risks, and present findings to management to streamline operations and improve quality.

As an Enterprise Account Executive at Salesforce, you will drive revenue growth by leveraging AI-driven solutions, understanding client needs, and demonstrating how Agentforce can solve business challenges while fostering client relationships.

The Senior Product Manager will lead the development of The Trade Desk's infrastructure, focusing on scalability, security, and optimizing complex systems to support high-performance workloads. Responsibilities include modernizing core systems and collaborating with cross-functional teams to enhance product capabilities and performance.

Lead Data Scientist partners with business stakeholders to solve problems using data: curate and analyze large datasets, build and deploy statistical and machine learning models, run experiments and causal analyses, develop dashboards, automate workflows, mentor junior staff, and operationalize scalable AI/ML solutions to drive measurable business value.

Design, build and operate highly scalable AWS-based data systems and streaming applications. Collaborate with data scientists to integrate ML models, deliver ETL/data flow and enrichment pipelines, follow secure coding and compliance standards, participate in full Agile lifecycle, produce documentation, and lead/mentor engineering peers from ideation to production.

The Data Scientist II will design, build, and deploy machine learning models and data products, translating business problems into data-driven solutions, while collaborating with various stakeholders and ensuring reliable, production-ready outcomes.

The Director of Robotics Product Safety leads safety vision and execution for autonomous systems, ensuring compliance and risk management, while mentoring the safety engineering team.

Lead enterprise data and analytics strategy for a pharmaceutical company, building cloud-native data platforms, governance, and AI/ML capabilities. Partner with senior leaders, oversee data engineering, integrations (Veeva/Salesforce), vendor relationships, budgets, and a high-performing team to deliver executive insights and self-service analytics while ensuring regulatory compliance.

The Sr. Product Manager will own product strategy and execution for key initiatives, collaborating with cross-functional teams and focusing on AI and e-commerce solutions.

Lead the development and implementation of machine learning solutions, managing a team to drive strategic decisions and innovative business outcomes.

Lead GenAI strategy and research to develop scalable LLM and agentic AI applications (e.g., conversational assistants). Analyze data to personalize investment outcomes, collaborate with engineers, productionize models, ensure best practices in data management and evaluation, publish research, and mentor applied scientists.

Lead AI/ML product strategy and execution: translate business needs into scalable, secure AI-enabled solutions; define product vision and governance; prioritize and manage backlog; partner with engineering, data science, and platform teams; ensure technical soundness, MLOps readiness, and regulatory/responsible AI alignment; drive delivery, adoption, and measurable business value from ideation through launch and post-launch evaluation.

As an AI/ML Engineer, you will develop multimodal AI models, focusing on computer vision and agentic capabilities. Responsibilities include data curation, model training, evaluation, and deployment while working with real robotic systems.

The AI/Machine Learning Engineer II will design and develop models to analyze data for health monitoring devices, focusing on diagnosis and prediction using various algorithms.

Design, research, and implement Generative AI models to enhance investment processes. Collaborate with teams to deliver enterprise-grade solutions and lead projects while solving complex machine learning problems.

Lead strategy, design, implementation, and optimization of Salesforce Marketing Cloud, Data Cloud, and related digital/website systems for pharma marketing. Partner with marketing, agencies, and vendors to build omnichannel campaigns, integrations, analytics, and ensure regulatory compliance while managing deployments, UAT, and platform architecture.

Deploy, maintain, and improve production ML workflows and platforms for media measurement and customer analytics on AWS. Build SageMaker jobs and endpoints, orchestrate pipelines with Step Functions, Lambda, and Airflow, manage model artifacts and CI/CD, troubleshoot production issues, and collaborate on platform enhancements and operational best practices.

Design, develop, and deploy scalable machine learning models and data pipelines for production. Collaborate with data scientists, engineers, and stakeholders, optimize model performance and scalability, automate deployments, monitor production systems, and evaluate emerging ML and cloud technologies to drive business outcomes.