Top Senior Machine Learning Jobs in San Diego, CA

Lead design and scaling of a unified fraud and risk platform. Define product strategy, own fraud metrics, run SQL-driven analysis and A/B tests, and partner with engineers and data teams to build real-time detection, identity verification, and transaction monitoring. Balance customer experience with risk mitigation and communicate impact to executives, legal, and partners.

Lead design, build, and operate an end-to-end Identity Platform for KYC/KYB, overseeing CIP, CDD, sanctions screening, and continuous risk monitoring. Drive AI-first automation to reduce manual reviews, mentor engineers, manage reliability and incidents, and represent technical solutions to customers and regulators. Partner cross-functionally to shape roadmap and ensure regulatory compliance and extensibility across jurisdictions.

The Sr. Machine Learning Engineer will develop and deploy ML solutions for healthcare, manage data pipelines, and work with large datasets to enhance healthcare delivery.

As a Staff Applied ML Scientist, you will develop and maintain fraud detection models, conduct research on fraud types, and collaborate across teams to drive product development and real-time decision-making.

As a Senior Applied ML Scientist, you'll develop fraud detection models, research new fraud types, and write production code while collaborating across teams to enhance SentiLink's identity verification solutions.

The Enterprise Account Executive drives revenue through high-value contracts, managing complex sales processes and relationships with executive stakeholders in financial services.

Lead QA for cloud-native AI/ML platforms: define test strategies, build and maintain automated test suites, validate data pipelines, models, and infrastructure (IaC), integrate tests into CI/CD, perform observability and non-functional testing, and collaborate with data scientists, engineers, and vendor teams to ensure reliability and scalability.

Design, deploy, and maintain end-to-end ML risk solutions at scale to detect and prevent fraud, merchant risk, and credit loss. Partner with cross-functional teams, lead technical decisions, build ML tooling, monitor models in production, and investigate emerging abuse patterns to improve detection and decisioning.

Lead Data Science initiatives, build AI/ML solutions, and mentor teams in a collaborative environment, driving innovation in a leading construction equipment venture.

The Director of Computer Vision will lead technical vision, research, and execution in developing scalable AI-driven computer vision solutions, managing teams, and enhancing performance metrics.

The Senior Product Manager will set product direction, own the development lifecycle, collaborate with teams, and ensure high-quality outputs. This role requires strong opinions on product quality and customer insights.

Lead the Decision Science function, designing ML models, overseeing experimentation frameworks, and ensuring model adoption across the company, driving operational and commercial improvements.

The Senior Developer Relations Manager will engage with developer ecosystems in agriscience, driving the adoption of NVIDIA technologies through technical guidance, collaboration, and strategic advocacy. Responsibilities include advising on resources, onboarding partners, monitoring ecosystems, and collaborating across functions to promote successful integrations.

Lead design and delivery of a unified, real-time billing platform that embeds AI/ML to automate reconciliations, detect anomalies, enable predictive insights, and create autonomous finance workflows across global billing operations.

Lead and scale engineering teams building Protect, a real-time multi-signal fraud detection platform. Set technical strategy, develop managers and senior engineers, deliver distributed systems and APIs, improve architecture, observability, reliability, and developer productivity while partnering with Product, Research, Security, and exec stakeholders.

The Staff Product Manager will define product strategy, lead the product lifecycle, collaborate across teams, and drive innovation in claims processing software.

The Director of System Safety oversees safety functions for autonomous vehicles, managing safety cases, deployment plans, and regulatory relationships while leading a multi-disciplinary safety team.

The Senior Technical Product Manager will lead the roadmap for Aledade's AI Data Platform, collaborating with various teams to enhance AI capabilities and improve healthcare outcomes for patients.

Lead a team of analysts to advance fraud and safety operations through analytics, ensuring robust data products and compliance while empowering stakeholders with actionable insights.

The Director of Software Engineering will lead teams in creating innovative education tech solutions, strategic planning, and optimizing software delivery processes.

Own a product area of the Content Authoring Platform end-to-end: set vision and roadmap, run continuous discovery, define and measure outcomes, partner with engineering and design to deliver features, evaluate and apply AI capabilities prudently, mentor peers, and communicate strategy and trade-offs to stakeholders.

Lead enterprise design and deployment of a global operating model for bovine IVF production. Drive standardization, SPC, automation, AI/analytics, Lean/Six Sigma, quality systems, and continuous improvement to scale consistent, high-throughput production across labs and field operations.

Lead and coordinate end-to-end fraud risk engagements, structure analytical solutions, guide analytics teams, communicate with clients and senior stakeholders, manage timelines, build fraud rules/governance, and identify additional client opportunities.

Lead development of time-series and econometric models (ARIMA, VAR, state-space, WLS, panel data) and Bayesian probabilistic frameworks. Use causal inference and stochastic processes to produce actionable insights, work with large datasets on Databricks, communicate results to stakeholders, and mentor junior team members.

Design, develop, and maintain high-performance, secure Java backend services and APIs. Ensure reliability, scalability, and cost-efficiency across microservices, databases, messaging systems, and capacity planning. Troubleshoot, profile, benchmark, and optimize systems (including ML applications) and collaborate with Kazakhstan stakeholders.