Top Senior Machine Learning Jobs in San Diego, CA

Lead credit and funding decisioning for auto lending partners, exercising delegated lending and funding authority, resolving exceptions and stipulations, feeding performance insights to product and risk teams, conducting win/loss analysis, and enabling dealer-facing operations and training to protect portfolio performance and improve approval workflows.

Lead design, development, and deployment of end-to-end recommendation systems. Build, tune, and evaluate scalable recommendation algorithms, integrate ML into products, lead projects, mentor teams, and communicate solutions to clients and stakeholders while driving innovation in replenishment and supply chain analytics.

Manage a portfolio of enterprise and mid-market North American customers to drive adoption, retention, expansion, and measurable ROI for Jumio's identity verification SaaS. Monitor health signals, build success plans, lead business reviews, partner cross-functionally, handle escalations, and ensure customers achieve outcomes tied to renewals and expansion.

Lead Buildertrend's end-to-end payments risk and operations: merchant onboarding, underwriting, transaction monitoring, disputes, chargebacks, and portfolio management. Build AI-assisted fraud prevention, scale automation, embed risk controls with Product and Engineering, develop analytics and governance, and grow a high-performing team to balance risk and business growth.

As a Staff Machine Learning Engineer, you will design AI products on Edge devices, optimize ML model performance, and work with large-scale datasets, collaborating across teams to deliver impactful solutions.

As an ML Ops Infrastructure Engineer, you will design CI/CD pipelines for ML, maintain deployment systems, and implement monitoring while collaborating with research teams to ensure model quality and performance.

As a Systems Architect, you'll define and drive the infrastructure architecture for AI/ML workloads, design multi-cloud strategies, manage compute orchestration and storage systems, and lead capacity planning, while also collaborating with engineering leadership.

The engineer will build and operate AI/ML infrastructure, managing services on AWS and bare metal, using tools like Kubernetes and Terraform.

The Senior Clinical Informatics Sales Specialist drives adoption of informatics products by providing technical expertise, engaging with healthcare leaders, and developing sales strategies for genomic data analytics.

Lead end-to-end research applying advanced ML/DL (transformers, GNNs, RL, ensembles) to generate alpha across digital asset markets, build production-grade pipelines, prevent leakage/overfitting, analyze microstructure and on-chain data, and mentor junior researchers.

The AI Sales Executive drives new business growth and expands client relationships by selling AI-driven solutions for engineering and manufacturing sectors, managing the full sales cycle with a consultative approach.

Own and implement end-to-end product features across the stack (React/TypeScript front end, Ruby on Rails backend, relational DBs, GCP infra). Design APIs and data models, ensure performance and reliability, integrate AI/LLM-powered features, collaborate with product/design/clinical teams, perform code reviews, and mentor junior engineers.

Own Oscilar's AML product suite (transaction monitoring, KYC/KYB, screening, case management, SAR filing, AI agents). Define detection rules, model calibration, data strategy, and defensible audit trails. Collaborate with engineers and compliance, use AI across discovery/design/analysis, deliver PRDs, validate models, and ship production features.

Lead the data and ML product vision: define roadmap, prototype models on noisy behavioral datasets, translate signals into user-facing features, partner with engineering to productionize ML, and generate insights to inform product roadmaps.

Lead high-impact strategy and BizOps workstreams including M&A diligence, investor relations, new-market expansion, and cross-market operations. Frame ambiguous, board-level problems, build analysis and recommendations, align stakeholders, and own execution end-to-end while leveraging AI and automation.

Conduct ML research for query understanding, ranking, clustering, and AI-powered search. Prototype and productionize algorithms, define data and evaluation requirements, design scalable systems, collaborate with engineers, run experiments, and publish patents/papers to integrate state-of-the-art ML into Yahoo Search products.

Lead and extend EnergyHub's platform for managing distributed energy resources and VPP dispatch controls. Conduct customer and market research, define and prioritize features, validate hypotheses, respond to client data requests, and collaborate with product, engineering, data science, sales, and client success to deliver strategic and incremental product improvements.

Own OEM-facing product roadmap for the Automotive Enterprise Cloud, translate OEM requirements into scalable integrations (APIs, data pipelines, reporting), lead discovery and delivery with cross-functional teams, define success metrics, produce product artifacts, and drive OEM adoption and satisfaction.

This role involves leading strategic planning, product innovation, and cross-functional collaboration to enhance pharmacy analytics and drive growth initiatives for CVS Health.

As Director of AI/ML, lead the ML organization, set technical vision, mentor a high-performing team, and contribute to model development and production deployment.

Lead the Client Solutions team, ensuring the execution of complex transactions while driving innovation and client advocacy. Oversee operations, build client relationships, and implement strategic frameworks for growth.

The Director of Data Sciences leads a team in strategic initiatives, drives machine learning and AI solutions, and manages resources to enhance data-driven decision making across the business unit.

The AI & Data Science Director will lead AI strategies, foster technical leadership, support team development, and integrate generative AI into products.

Lead development of an AI-enabled Ethereum Layer 2 platform: build front-end and back-end systems, deploy and optimize AI models, create data pipelines, collaborate on model training, and contribute to product innovation and other company projects.

Serve as primary post-sales relationship owner for federal customers, driving onboarding, adoption, and retention of HiddenLayer cybersecurity/AI solutions. Coordinate cross-functional teams, conduct business reviews, mitigate risks, capture customer feedback, and support renewals and expansion in complex federal environments.