Top Machine Learning Jobs in San Diego, CA

Partner with healthcare clients to design, prototype, and deploy production-grade AI/LLM solutions. Lead discovery, architecture, cloud integration, and delivery while troubleshooting distributed systems and driving measurable client outcomes.

Build and deploy scalable AI and machine learning products for clinical research, including patient recruitment, enrollment forecasting, and study feasibility. Develop ML models, LLM-powered agents, data pipelines, and MLOps infrastructure using cloud services and CI/CD automation. Collaborate with cross-functional teams to integrate AI into clinical research workflows, monitor model performance, and advance reliable, unbiased solutions that improve patient outcomes.

Leads Yahoo’s Detection Engineering team within Threat Detection and Response. Responsibilities include developing cybersecurity detection strategy, managing detection engineers, building and maintaining detection rules, supporting investigations, conducting threat hunting and purple-team activities, integrating threat intelligence, and applying data science and AI to identify adversaries. The role also guides sprint delivery, researches emerging threats, and collaborates with security leadership, incident response, insider threat, and advanced cyber threat teams.

Own and prioritize the product backlog, facilitate Agile ceremonies, write user stories and functional specifications, define acceptance criteria, and align engineering, design, and stakeholders. The Product Owner tracks delivery progress, oversees testing and validation, incorporates user feedback and performance metrics, and improves team workflows through clear documentation and proactive communication.

The Senior Data Scientist will analyze large-scale customer data, investigate behavioral questions, design and automate studies, and translate findings into actionable recommendations. The role includes maintaining analytics frameworks, documenting methodologies, writing white papers, and communicating insights across the company. Candidates should be independent, comfortable with ambiguity, and experienced with SQL and Redshift. Python or R, machine learning, Spark, A/B testing, and cross-functional experience are preferred.

Lead product design for Fetch’s Receipt & Rewards experience, connecting receipt capture, account linking, recognition, matching, and rewards. Define design strategy for complex, AI-enabled systems; improve usability, accessibility, trust, and experience quality; and balance user needs, data quality, business goals, and technical constraints. Partner with Product, Engineering, Research, and Data Science, drive cross-functional alignment, shape multi-quarter initiatives, and mentor designers.

Design and deploy production recommendation and retrieval engines, build data orchestration pipelines for multiple modalities, implement agentic workflow frameworks, and prototype, optimize, and scale models with monitoring, governance, and low-latency SLAs.

Lead the roadmap and delivery of an AI data platform supporting internal teams and external healthcare products. Manage ML and LLM platform workstreams across data ingestion, training, deployment, monitoring, and workflow optimization. Partner with AI engineers, researchers, data scientists, clinical leaders, and business stakeholders to define requirements, develop user stories, validate model performance, and turn proofs of concept into scalable production capabilities.

Build privacy and anonymization systems that detect and transform PII, credentials, secrets, and other sensitive information in data used for AI training. Develop detection methods combining rules, statistical models, classifiers, and LLMs; create production data-processing pipelines; evaluate privacy risk and retained utility; and ensure robustness against schema drift, unusual formats, leakage, and adversarial re-identification.

Leads the evaluation, design, development, and deployment of production AI/ML applications in AWS environments. Builds and optimizes machine learning models, assesses emerging technologies, presents technical recommendations, collaborates with federal clients, and mentors engineering teams. The role also supports cloud-native development, operations, security, enterprise AI adoption, and experimentation involving modern AI platforms and practices.

Provide legal support for commercialization and product development of an AI-powered ad tech platform: draft and negotiate commercial agreements, manage IP portfolio and complex IP litigation, advise on AI, data, and privacy matters, counsel product teams on compliance and IP protection, and develop automated legal workflows.

Develop and maintain Power BI dashboards, reports, data models, KPIs, and executive scorecards using SQL and healthcare claims data. Analyze trends, anomalies, savings opportunities, compliance risks, and Payment Integrity performance. Partner with business, compliance, clinical, and technology stakeholders to translate requirements into scalable regulatory and operational analytics solutions. Ensure data quality, governance, and reporting consistency while supporting forecasting, root cause analysis, and AI-enabled analytics initiatives.

Leads client services and cross-functional delivery teams supporting enterprise software implementations. Oversees end-to-end project execution, client relationships, business-process transformation, stakeholder education, requirements documentation, and ongoing value delivery. Applies revenue growth management expertise across pricing, trade promotions, assortment, or supply planning, while collaborating with technical teams on AI, machine learning, and analytics solutions.

Own product marketing for Gladly’s Agent Harness and AI Core platforms. Develop technical positioning, messaging, launch strategies, sales enablement, competitive intelligence, and narrative assets. Translate AI agent behavior, evaluation, steering, and measurement into credible messaging for CX leaders and technical buyers. Manage tier-one launches end to end while balancing two product areas as a senior individual contributor with minimal oversight.

Leads and develops a perception and machine learning engineering team building computer vision, sensor fusion, tracking, detection, and scene-understanding capabilities for autonomous systems. Owns roadmap planning, technical decisions, delivery, model development and deployment workflows, field readiness, hiring, performance management, and cross-functional execution with autonomy, embedded, data, hardware, product, programs, and field operations teams.

Part-time contract copywriter creating persuasive, compliant, on-brand messaging for a credit card product across email, paid media, social, web, and in-app channels. Responsibilities include communicating benefits, rewards, fees, and terms; developing lifecycle and educational content; maintaining brand voice; collaborating with Marketing, Creative, Product, Legal, and Compliance teams; and managing multiple campaigns under tight deadlines.

Lead VSolvit’s Alliant 3 task-order growth strategy by building and managing the opportunity pipeline, qualifying pursuits, analyzing Alliant 2/3 recompetes, and establishing repeatable capture and review processes. Develop Navy-focused opportunities, coordinate with business development, capture, and technical leaders, and deliver measurable milestones during an initial 90-day program.

Develop and deploy machine learning models for manufacturing use cases including predictive quality, machine failure prediction, and time-series pattern discovery. Work directly with customers to scope problems, validate solutions in live deployments, and translate successful analyses into product features. Collaborate with engineering, product, and customer success teams while applying statistics, optimization, generative AI, and agentic AI to deliver end-to-end solutions.

Analyzes complex healthcare data to identify trends, develop statistical and machine learning methodologies, and produce actionable insights. Builds dashboards and reports, supports product and business decisions, promotes data literacy, and collaborates with cross-functional teams. The role also ensures analytics practices comply with healthcare privacy, governance, security, and regulatory requirements, including HIPAA.

Lead the architecture and delivery of production-grade AI/ML systems for client engagements. Design agentic AI, LLM, RAG, search, recommendation, and classical machine learning solutions; advise client stakeholders; mentor engineering teams; oversee technical strategy, project delivery, deployment, monitoring, and iteration across AWS and GCP environments.

Leads commercial growth execution as the CCO’s operating partner, orchestrating go-to-market programs across Sales, Marketing, Customer Success, Partnerships, and Operations. Establishes execution frameworks, operating rhythms, accountability systems, KPI dashboards, and performance reporting. Aligns cross-functional leadership, scales sales motions, identifies capability gaps, removes execution barriers, and drives measurable revenue, customer, and market growth initiatives.

Owns product vision, strategy, roadmap, and execution for Yahoo Search monetization across traditional and AI-powered search. The role optimizes sponsored search relevance, ranking, placement, coverage, revenue, and user experience while developing new advertising formats for conversational and generative experiences. Responsibilities include experimentation, marketplace analysis, performance measurement, partner collaboration, and close work with engineering, data science, analytics, and design teams.

Design and implement enterprise AI architectures spanning GenAI, machine learning, RAG, agentic workflows, data pipelines, APIs, and production deployments. Build Python prototypes and AI services, define governance and evaluation frameworks, integrate models with enterprise platforms, and guide engineering teams through implementation. The role requires hands-on expertise with LLM applications, orchestration frameworks, model lifecycle management, monitoring, security, and scalable production AI systems, preferably in financial services.

Design, build, and maintain optimization technology, full-stack systems, and data-intensive scheduling infrastructure. Improve optimization algorithms using linear optimization, machine learning, and generative AI. Lead complex technical initiatives, establish testing and observability, support scalable operations, troubleshoot customer issues, participate in on-call rotations, and mentor engineers while partnering closely with product and engineering teams.

Own the production runtime for Phare’s machine learning stack by deploying, serving, and scaling models across GPU inference endpoints and batch or streaming workflows. Build progressive delivery pipelines, automated rollbacks, observability, alerting, and incident response processes. Manage model registries, retraining lifecycles, versioning, data lineage, security controls, and reproducible releases using Kubernetes, Terraform, Docker, and CI/CD.