Top Senior Machine Learning Jobs in San Diego, CA

Lead design, build, and deploy scalable, reliable Java-based microservices in a cloud-native, event-driven AWS environment. Own backend feature design, code quality, automated testing, and FedRAMP release processes. Mentor engineers, participate in on-call/TechOps, integrate AI tools into development, and drive architecture, observability, and cross-team initiatives.

As a Customer Success Engineer, you'll drive adoption and satisfaction for enterprise customers using Deepgram's voice AI technology, fostering strong relationships and aligning technical solutions with business objectives.

Lead and manage the underwriting and credit risk model validation team, perform hands-on independent validations of complex ML models, assess data integrity and performance, identify and remediate model weaknesses, partner on MRM framework improvements, and coordinate with audit, compliance, and controls to meet regulatory standards.

Lead the development of machine learning systems for Cedar Pay's Personalization Engine, manage ML engineers, and ensure ML model effectiveness.

The Staff Machine Learning Engineer will lead ML initiatives, develop ML systems, collaborate with cross-functional teams, and mentor junior engineers to optimize healthcare intake workflows using advanced machine learning techniques.

Lead and transform the Fraud Intelligence Team by designing scalable operating models, QA and measurement frameworks, and talent programs. Drive labeling quality, operational metrics, and fraud prevention impact; convert frontline fraud observations into insights for Product, R&D, Analytics, and GTM; leverage AI, automation, and tooling; and serve as a cross-functional fraud subject-matter expert while developing early-career talent and measurable business outcomes.

Lead product vision and roadmap for the Hivemind AI Platform to enable training, evaluation, governance, and safe edge deployment of foundation and domain models. Drive MLOps, data/simulation pipelines, synthetic data generation, model governance, and integration with edge hardware. Partner cross-functionally to productionize research, ensure accreditation and safety, and support continuous learning and sovereign AI factory capabilities for mission-critical autonomy.

Senior-level engineer delivering analytics and ML-Ops solutions for healthcare payers. Design and implement analytics platforms on Databricks, develop CI/CD and provisioning patterns, collaborate with data scientists, mentor juniors, and build client relationships to drive actionable insights and operational improvements.

Lead design and implementation of Headway's insurance systems (eligibility, pricing, matching, claims). Build data-intensive, ML-powered platforms and automation, mentor engineers, write high-impact code, and improve accuracy and reliability across state and payer complexity to scale insurance-covered therapy.

Lead AI-focused audits, advisory reviews, and investigations to detect misuse, fraud, unauthorized activity, data leakage, and compliance violations. Analyze AI system data, prompts, outputs, logs, access patterns, workflows, and control evidence; document findings, recommend remediation, support audit planning, and conduct follow-up testing. Collaborate with technology, compliance, legal, privacy, HR, security, and business stakeholders while maintaining audit independence and evidence integrity.

Lead product analytics to inform strategy and optimize user experience: translate business questions into analysis, build reliable analytics infrastructure, run A/B tests and ML/statistical analyses, track funnels and cohorts, support 0-to-1 product launches, and communicate actionable insights to cross-functional teams.

Founding Product Engineer will build a vision-based Physical AI product end-to-end: device-to-cloud systems, real-time event ingestion and storage, multi-tenant access control, dashboards and workflows, and agentic/LLM-driven features. Work directly with customers, run pilots, and iterate rapidly across infrastructure and product surfaces.

Lead and build the Applications function to translate clinical/research lab workflows into validated, deployable robot capabilities. Own workflow validation, instrument onboarding, training data collection for ML, technical documentation, demos, customer technical leadership, and team hiring and development.

Lead a team of ML engineers to develop fraud detection models, defining strategies, driving model evolution, and ensuring effective integration with cross-functional teams.

Triage AI opportunities, shape technical solutions, write precise SOWs and internal handovers, identify reuse vs. new engineering, and coordinate sales and engineering to deliver scoped AI engagements (5–10 concurrently, 30–45 day cycles). Ensure delivery-ready documentation and flawless handoffs to implementation teams.

You will tackle AI challenges, develop scalable software and collaborate with teams to enhance healthcare navigation using AI solutions.

Lead and transform the Fraud Intelligence Team into a high-impact function by improving operating models, QA, tooling, and metrics; build entry-level talent programs; connect labeling to measurable fraud prevention outcomes; deliver actionable insights to Product, R&D, Analytics, and GTM; and leverage AI and automation to increase productivity and business impact.

Partner with functional leaders to translate business strategy into people strategy. Own org design, performance management, compensation, talent development, engagement, and retention. Provide coaching on career pathing, change management, and sensitive employee issues. Use people data to generate insights and recommendations, build compliant HR policies, manage global employee relations, and collaborate with People Team COEs to deliver cohesive people programs at scale.

Serve as second-in-command for Coinbase Derivatives' Market Regulation Department, leading day-to-day regulatory compliance, managing exams and audits, advising on CFTC Core Principles, reviewing surveillance escalations and enforcement actions, and coordinating cross-functional regulatory workstreams to ensure the DCM meets obligations and resolves findings timely.

The Staff Machine Learning Engineer will design and build scalable ML systems, mentor engineers, and drive AI strategy at SailPoint, focusing on AI-powered identity security solutions.

Lead strategy, vision, and roadmap for a cross-functional squad across Everand and Fable. Drive product development for recommendations, search, and ranking systems, balance experiments and large investments, partner with engineering, design, research, and data to ship features that help readers discover books.

Apply and optimize advanced ML models (including multimodal transformers) to support drug discovery. Collaborate with chemists and biologists, evaluate models, integrate ML insights into design-make-test-analyze cycles, communicate results internally and externally, and guide ML model evolution with domain-driven feedback.

Lead Software & AI Engineer responsible for designing, developing, and deploying software solutions integrating AI/ML. Requires extensive experience in cloud-native development and DevSecOps.

Provide legal guidance on Rubrik's AI use and products, ensuring compliance with laws and contracts, drafting and negotiating AI terms, coordinating generative AI review processes, educating employees, and improving AI review controls and workflows across cross-functional teams.

Develop and integrate software and AI capabilities for Navy expeditionary systems, including sensors, unmanned systems, command-and-control platforms, and Tactical Assault Kit. Build tactical applications, maintain real-time data meshes and pipelines, normalize tactical data, test field systems, and integrate machine learning models. Collaborate with data and systems engineers, troubleshoot operational systems, monitor data reliability, and provide technical guidance for long-term Department of the Navy technology strategies.