Machine Learning Jobs in Santa Ana, 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.

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.

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.

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 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 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 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 underwriting strategy for AI-enabled products, identify and manage title insurance and model-related risk, advise product/engineering/data teams, ensure regulatory and underwriting compliance, liaison between transaction underwriters and product teams, mentor junior counsel, and contribute to enterprise product underwriting principles.

Lead PRP's Accounts Payable Recovery Audit practice, managing the end-to-end audit lifecycle, P&L performance, client engagements, and a team of managers and analysts. Use analytics, automation, ERP/AP tools, and benchmarking to identify overpayments and recover funds, negotiate with vendors, present findings to finance leaders, and drive process improvements and business development.

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.

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.

Design and build distributed ML infrastructures to optimize data processing, model training, and evaluation among teams.

Lead design, implementation, optimization, and administration of scalable database systems and AI/ML data infrastructure. Build vector DBs, embedding stores, RAG architectures, ETL pipelines, and integrations with LLM APIs. Provide technical leadership, performance tuning, security, data governance, and support for AI-enabled applications while mentoring junior staff and driving data quality and monitoring.

Design and implement 3D machine learning models, process reality capture data, and integrate AI solutions in production environments for robotics applications.

As a Senior Machine Learning Platform Engineer, you will manage ML infrastructure, optimize pipelines, mentor junior engineers, and ensure observability and compliance in production environments.

Support design, training, evaluation, deployment, and monitoring of ML models for document classification, entity extraction, and outcome prediction. Help integrate AI tools into legacy workflows, track metrics (precision/recall/accuracy), assist model versioning and logging, and collaborate across teams while gaining hands-on experience with tax-focused AI systems.

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.

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.