Top Senior Machine Learning Jobs in San Diego, CA

Lead go-to-market strategy for Sprout Social’s AI portfolio, including the Trellis AI agent. Develop enterprise launch playbooks, positioning, executive messaging, campaigns, and enablement programs. Analyze market and competitive dynamics, influence product roadmaps, improve launch processes, and partner with Product, Sales, Revenue, Brand, and executive leadership to drive adoption, revenue growth, deal expansion, and category leadership. The role also mentors marketing team members and operates with substantial autonomy.

Lead agile design and development projects for mobile apps and digital products. Coordinate product, design, engineering, marketing, leadership, and client stakeholders; manage project plans, scope, requirements, backlogs, acceptance criteria, deadlines, workflows, and deliverables. Support scoping and client relationship management while ensuring successful end-to-end software launches and alignment with business objectives.

Lead AI engineering teams to design, build, and deploy end-to-end AI solutions. Manage client relationships, plan and deliver projects, mentor staff, drive adoption of cloud-native microservices, CI/CD, vector databases and orchestration tools, and ensure high standards of quality, innovation, and compliance.

Develop and operate production ML and AI systems powering patient experiences such as matching, ranking, recommendations, onboarding, and personalization. Build reusable ML infrastructure, pipelines, evaluation, observability, and model-serving capabilities. Provide technical leadership across the ML lifecycle, guide architecture, evaluate custom versus foundation-model approaches, and partner with ML and Patient Engineering teams to deliver reliable, scalable AI products.

Leads the AI Engineering team across applied AI features and foundational ML infrastructure. Responsibilities include managing Senior and Staff engineers, hiring and coaching, deploying LLM-powered capabilities, building MLOps and AI observability platforms, balancing product delivery with platform investment, and ensuring privacy, compliance, evaluation rigor, and clinical safety in production systems.

Own the strategic vision and roadmap for Coursera’s AI-driven search experience. Lead conversational search, personalization, semantic and multilingual search, ranking, and discovery improvements. Partner with engineering, design, research, data science, ML, marketing, and partnerships teams to deliver scalable platform capabilities. Use experimentation, market analysis, KPIs, and customer insights to improve conversion, merchandising, learner experience, and revenue.

Set the technical vision for data science, lead complex statistical and machine learning model development from concept through production, and architect scalable modeling platforms and pipelines. Develop credit risk, pricing, and loss forecasting models; establish model governance standards; partner with senior leaders; mentor data scientists; and communicate technical strategy to executives. The role emphasizes production deployment, monitoring, cloud architecture, and high-impact decision-making across the business.

Owns analytics and optimization strategy for advertising revenue across Zynga’s mobile game portfolio. Responsibilities include monitoring performance, diagnosing trends, designing A/B tests, identifying monetization opportunities, partnering with product, analytics, and data science teams, supporting AI and ML models, leading cross-functional initiatives, and mentoring analysts.

Develop and maintain production machine learning models, build scalable training and serving technologies, optimize real-time and batch ML pipelines, and monitor model performance and drift. The role involves deep neural networks, recommendation systems, automated retraining, ML research, engineering excellence, and communicating technical concepts to diverse audiences. Candidates need 6+ years of industry ML experience, strong coding skills, and experience deploying neural networks at scale.

Build and operate production machine learning systems enabling autonomous medical coding at scale. Responsibilities include data discovery, feature engineering, model training and evaluation, deployment, monitoring, MLOps pipelines, LLM integration, observability, governance, fairness assessment, and A/B testing. The role also involves designing highly available low-latency architectures, defining technical roadmaps, and collaborating with product, design, data, and platform teams.

Lead computational science efforts for small-molecule discovery programs focused on protein homeostasis. Apply computational chemistry, cheminformatics, machine learning, structural modeling, and data analysis to design and prioritize degraders and molecular glues. Develop predictive models and reusable workflows, integrate structural and biological data, steward computational resources, and influence project strategy. Provide scientific leadership, mentorship, and external visibility through publications, presentations, and patents.

Designs, builds, and scales enterprise AI applications using classical machine learning, generative AI, RAG, and agentic architectures. Develops intelligent workflows, autonomous agents, knowledge systems, chatbots, copilots, and decision-support solutions integrated with enterprise platforms and APIs. Leads AI governance, evaluation, observability, security, and human-in-the-loop controls while advising clients on enterprise AI transformation. Requires extensive experience with Claude, OpenAI, LLMs, cloud platforms, vector databases, semantic search, and production-grade AI implementations.

Product Counsel will advise product, engineering, data science, marketing, compliance, and sales teams throughout the product lifecycle. Responsibilities include counseling on regulatory compliance, privacy, intellectual property, consumer protection, AI and machine learning, data rights, platform architecture, APIs, identity and account security, and marketing. The role translates legal requirements into technical guidance, supports AI governance, monitors evolving laws, and develops scalable legal processes for a fast-paced technology company.

Provides senior functional and technical support for Navy and Marine Corps logistics information systems. Oversees AIS operations, system administration, database performance, testing, troubleshooting, user access, audits, data integrity, upgrades, training, and business process improvements. Supports requirements generation, data migration, software integration, and data science initiatives while mentoring analysts. Requires extensive Navy logistics AIS experience, Secret clearance, Unix/Linux familiarity, and travel to domestic and overseas military locations.

Serves as senior functional owner for Workday Time Tracking, Absence, Benefits, and payroll integrations. Leads configuration, solution design, requirements, testing, reporting, data reconciliation, security controls, releases, and global HR technology initiatives. Diagnoses complex system and interface issues, creates operational documentation, manages risks and dependencies, and coaches analysts and project teams while partnering with Payroll, Benefits, Finance, Technology, Audit, and vendors.

Design, build, and support high-throughput, low-latency LLM inference and data pipelines; collaborate with data scientists to post-train and evaluate models; implement scalable, production-ready systems with strong testing, monitoring, and performance focus; mentor engineers and iterate on architecture, reliability, and user-facing AI applications.

Build GCP data pipelines, ETL/ELT processes, integrations, data models, and analytics solutions. Support AI/ML development with Vertex AI and Gemini, including MLOps, prompt engineering, embeddings, and RAG experimentation. Participate in client requirements gathering, technical implementation, data governance, quality, security, monitoring, and documentation while collaborating with senior engineers and architects.