Machine Learning Jobs in Irvine, CA

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.

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.

Designs and advances the firm's enterprise data and analytics capabilities by building data platforms, warehouses, lakes, semantic models, pipelines, dashboards, and machine learning solutions. Develops AI-ready data assets, predictive models, reporting solutions, and governed analytics capabilities. Provides technical leadership in data architecture, governance, automation, emerging technologies, and analytics strategy while partnering with business and technology stakeholders.

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 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.

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.

Develop reusable ML tooling and libraries, collaborate with data scientists to productionize models, build services and APIs (Docker/Linux), follow engineering best practices, and support project lifecycle from intake to maintenance.

Provide legal counsel for Interventional Cardiology Therapies with focus on digital health. Advise digital health programs and software teams on regulatory, privacy, data protection, SaMD, AI/ML governance, and cybersecurity. Negotiate commercial and privacy agreements, support product lifecycle risk management, coordinate with Privacy, InfoSec, Regulatory, COEs and outside counsel, lead training, support transactions and M&A due diligence, and mentor legal team members.

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.

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.

Lead above-brand market analytics for neuroscience franchises, deliver actionable insights for brand strategy, harmonize data and reporting, enable HCP targeting and patient analytics, champion AI/ML-driven operations, and align cross-functional global teams to improve launch readiness and portfolio optimization.

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.

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 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.

Lead delivery and maturity of enterprise finance planning, forecasting, reporting, analytics, and data products. Build and coach a high-performing team, develop capability roadmaps, drive adoption of SAP Analytics Cloud and related platforms, and partner across Finance, Technology, and Data to deliver measurable business value through automation, advanced analytics, and scalable solutions.

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

Lead development and execution of enterprise AI strategy, governance, architecture, and adoption. Coordinate cross-functional teams to identify use cases, enable responsible AI, support implementations, measure business value, and drive enterprise-wide AI literacy and standards.

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 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.

Lead Data Scientist partners with business teams to solve problems using data: pull and analyze large datasets, build and deploy statistical and machine learning models, run experiments and causal inference, create dashboards, automate workflows, and mentor junior scientists. Works with data engineers to operationalize scalable AI solutions and communicates insights to non-technical stakeholders to improve efficiency, reduce costs, and enhance member experience.

Lead presales for data and AI initiatives: design and present Microsoft Fabric-based data platforms, run discovery and AI workshops, scope proposals, translate technical designs into business value, mentor delivery, and support go-to-market and thought leadership.

Lead hands-on analytics initiatives for Global Supply Chain using BI, ML/AI, and process improvements. Collaborate with stakeholders and IT to design, implement, and scale reporting, dashboards, POCs, and SOPs. Manage projects, train staff, and improve manufacturing data quality to drive operational performance.

Design, train, and deploy state-of-the-art deep learning models (transformers, CNNs) for end-to-end navigation. Build perception, prediction, and planning solutions, implement data pipelines, deploy and monitor models in production, detect drift, and troubleshoot integration and performance issues for real-world robotic systems.

Own program-level coordination across AI/ML research and engineering workstreams, tracking commitments, timelines, risks, blockers, and priorities. Translate customer and product requirements into internal plans, support customer deployments, communicate tradeoffs, and drive cross-functional resolution. Build lightweight reporting systems and partner with technical leaders without directing technical decisions. The role requires experience managing AI/ML programs, working with customers, and operating effectively in ambiguous, fast-moving environments.