Top Machine Learning Jobs in San Diego, CA

Leads Yahoo’s centralized CRM organization and owns the performance, strategy, governance, operations, innovation, and roadmap for email, push, SMS, newsletters, and other messaging channels. Oversees engagement, retention, revenue, deliverability, personalization, experimentation, quality, compliance, budgets, vendors, and cross-functional partnerships with Product, Engineering, Analytics, Legal, and Marketing. Develops senior leaders and scales AI-enabled CRM capabilities across Yahoo’s global consumer products.

Design, build, evaluate, and productionize machine learning and LLM-based agentic systems for healthcare products. Own projects end-to-end, including problem framing, dataset development, modeling, evaluation, deployment, monitoring, and safety guardrails. Build ML infrastructure, data pipelines, inference systems, and evaluation frameworks. Collaborate with clinicians, product managers, and engineers, while setting technical direction and mentoring team members.

Lead the design and development of Azure Compute Fleet capabilities that orchestrate Virtual Machine Scale Sets across regions. Build distributed control-plane services, APIs, and workflows for capacity placement, scaling, failover, and lifecycle management. Collaborate across Azure engineering teams, drive AI-enabled engineering improvements, participate in on-call operations, and improve reliability, observability, performance, and recovery for hyperscale cloud services.

Lead the engineering organization for BlueCat’s Network Observability product line. Own technical strategy, architecture, roadmap, delivery, and operational excellence for data-intensive network monitoring platforms spanning SaaS and on-premise deployments. Build AI-driven observability capabilities, modernize legacy systems, establish engineering standards, and develop distributed teams. Partner with product, executive leadership, customers, sales, and support to achieve business goals and resolve strategic technical issues.

Lead a team of bookkeeping professionals, manage client engagements and deadlines, build scalable bookkeeping processes, support client interactions, collaborate with engineering and product teams on accounting automation, and coordinate transitions to tax services. The role requires substantial client accounting services experience, team-building and process-development expertise, and close collaboration with tax advisors. CPA certification and startup experience are preferred.

Applied Data Scientist focused on incrementality, causal inference, experimentation, Marketing Mix Modeling, and predictive products. The role partners directly with customers to interpret data, diagnose measurement issues, explain statistical results, and provide actionable recommendations. Responsibilities include building diagnostic tools, analyzing model and experiment outcomes, improving methodologies and production capabilities, and collaborating with Product, Engineering, Media Strategy, Customer Success, and senior data scientists.

Leads the strategy, development, deployment, and performance of Stitch Fix’s recommendation, ranking, search, discovery, and personalization systems. Manages Data Scientists and Machine Learning Engineers, shapes cross-functional product roadmaps, drives offline evaluation and online A/B testing, and oversees the full production ML lifecycle. Advances generative AI and LLM-based evaluation while connecting model quality to client engagement, sales, revenue, margin, and satisfaction.

Designs and implements enterprise cloud and AI solutions for unstructured data workloads. Responsibilities include building ingestion pipelines, API integrations, document extraction and HITL workflows, tuning machine learning models, benchmarking performance, and ensuring security, availability, disaster recovery, and data isolation. The role also supports customer developers, leads technical proofs of concept, mentors engineering teams, develops reusable blueprints, and provides feedback to product engineering.

Owns end-to-end delivery of enterprise fine-tuning engagements, including client discovery, use-case prioritization, ROI, scope, timelines, model hosting, SLAs, security reviews, and stakeholder management. Partners with sales, product, engineering, and machine learning teams; navigates enterprise procurement and IT processes; translates between technical buyers and internal teams; and develops repeatable processes and playbooks to scale the practice.

Own and improve Headway’s privacy program across HIPAA, 42 CFR Part 2, state privacy laws, individual rights, incidents, vendor governance, and AI use. Maintain controls, data maps, metrics, training, and operational workflows. Conduct product, vendor, and AI privacy assessments; manage rights requests and incident investigations; coordinate notifications and regulatory submissions; and translate complex requirements into practical guidance for cross-functional teams.

Lead Risk Operations transformation programs from problem definition through implementation and measurement. Own automation initiatives, process redesign, tooling improvements, partner transitions, operational metrics, readiness, and continuous improvement. Collaborate with Risk Operations, Fraud Strategy, Compliance, Product, Engineering, Data, Shared Services, and Vendor Management to deliver measurable gains in service levels, quality, risk outcomes, backlog, and cost.

Own the strategy and roadmap for patient-provider search, retrieval, ranking, and marketplace matching. Lead experimentation, objective functions, evaluation, and ML platform foundations while partnering with ML engineers, data scientists, design, clinical teams, and executives. Improve successful, lasting care matches rather than optimizing only clicks or bookings. Balance patient access, provider growth, clinical quality, and payer priorities, while setting the standard for technically grounded product management.

Conduct research on frontier AI systems, including synthetic and agentic data generation, reinforcement learning, post-training, model understanding, benchmarking, and evaluation. Design rigorous experiments, datasets, prototypes, tooling, and research workflows; train and assess models; analyze results; and translate findings into scalable AI products. Collaborate across research, engineering, product, and operations teams, communicate technical conclusions, contribute to publications or open-source work, and mentor engineers and researchers.

Own the strategy and roadmap for Netflix’s scaled content ingestion, publishing, and distribution systems. Build automated, API-driven platforms that reduce manual workflows, support partner onboarding, enable reliable content fulfillment, and accelerate global time-to-launch. Partner with engineering, operations, design, data science, and business teams to translate complex operational needs into durable product capabilities and prioritize investments across high-scale media workflows.

Analyze product, user, transactional, and repayment data to develop risk and underwriting models, reduce losses and fraud, monitor model performance, and guide product and growth strategy. Build Looker dashboards and LookML models, conduct segmentation and experimentation, measure CAC and LTV, and communicate actionable insights to product, engineering, marketing, finance, and leadership.

Leads Imprint’s fraud prevention strategy across new account, first-party, and transaction fraud. Owns fraud loss outcomes, controls, team performance, and strategic priorities. Manages three fraud leads, partners with modeling and engineering teams, communicates risk and performance to executives, and serves as an operational backstop during severe fraud incidents. Requires deep money-movement fraud expertise, technical fluency in SQL, SAS, or Python, and experience leading fraud teams with loss or P&L accountability.

Build and scale accounting software synchronization solutions connecting BILL’s payment network with third-party accounting platforms. Lead end-to-end software design and delivery, develop scalable AWS microservices, improve platform performance, guide testing and CI/CD practices, resolve customer problems, mentor engineers, and use generative AI to accelerate development.

Drives underwriting innovation by designing, testing, and implementing new tools, technologies, strategies, and processes. Coordinates projects, manages deadlines and risks, supports user acceptance testing, and collaborates with IT, underwriting, data, product, operations, reinsurance, and vendors. Uses data analytics and machine learning to improve risk assessment, efficiency, and customer experience while ensuring regulatory compliance. Provides training and helps translate innovation concepts into adopted underwriting capabilities.

Lead development and productionization of telematics pricing and underwriting models. Responsibilities span statistical modeling, feature engineering, dataset and pipeline development, model deployment, monitoring, data quality validation, troubleshooting, regulatory support, and collaboration with pricing, actuarial, product, engineering, and compliance teams.

Own product positioning, messaging, segmentation, go-to-market strategy, competitive intelligence, customer proof, sales enablement, and thought leadership for Toloka’s enterprise AI data solutions and self-service platform. Translate complex AI and machine learning capabilities into differentiated customer value while partnering with product, sales, marketing, and customers.

Analyzes structured and unstructured datasets supporting U.S. Navy electronic warfare systems. Develops statistical, machine learning, NLP, data modeling, visualization, and reporting solutions to improve system readiness, reliability, maintainability, operational availability, and lifecycle performance. Integrates logistics, engineering, maintenance, and operational data; identifies trends and risks; and presents data-driven findings to technical and program stakeholders.

Develops analytical models and applications for U.S. Navy electronic warfare and sustainment systems. Applies data mining, statistical analysis, NLP, machine learning, and data modeling to structured and unstructured data. Integrates logistics, engineering, maintenance, reliability, and operational data to assess readiness, performance, risks, and availability. Creates visualizations, dashboards, reports, and briefings, while collaborating with engineers, logisticians, operations researchers, and program personnel to support lifecycle management and data-driven decisions.

The Sales Development Representative generates qualified pipeline through personalized phone, email, and LinkedIn outreach. Responsibilities include engaging decision-makers, qualifying inbound and outbound prospects, setting meetings, coordinating with account executives, maintaining Salesforce records, meeting pipeline targets, and improving messaging using performance data. The role also collaborates with Sales, Marketing, and Business Operations while developing expertise in identity verification, biometrics, fraud prevention, and digital banking markets.

Develop and implement AI-driven applications, workflows, integrations, and ServiceNow solutions across modules including ITSM, ITOM, CSM, and HRSD. Gather requirements, write and test code, configure REST/SOAP integrations, implement CMDB and Discovery capabilities, support impact mapping and event management, promote changes across environments, and remediate production incidents. The role also applies ServiceNow AI features such as Virtual Agent, Predictive Intelligence, Performance Analytics, and Now Assist.

Develop autonomy evaluation metrics, statistical and machine-learning analyses, dashboards, and pipelines for simulation and on-road autonomous vehicle testing. Analyze perception, prediction, and planning performance; identify anomalous behavior and critical scenarios; apply VLMs and LLMs where appropriate; and support release gating and safety decisions. The role requires production Python, C++ debugging, technical leadership, cross-functional collaboration, and rigorous software engineering practices.