Top Machine Learning Jobs in San Luis Obispo, CA

Designs and operates production multi-agent AI systems, LLM workflows, scoring and optimization algorithms, and closed-loop autonomous processes. Responsibilities include AI model evaluation, production monitoring, governance, third-party AI integration, federated data retrieval, and identifying patentable inventions. The role requires deep machine learning expertise, algorithm development, and deployment experience across complex operational environments.

As a Machine Learning Engineer, you will design, build, and deploy ML models for underwriting at Stripe Capital, ensuring performance while collaborating with multiple teams.

Lead end-to-end product strategy and delivery for a core marketplace area, collaborating with engineering, UX, and design. Conduct qualitative and quantitative research, run agile sprints, measure results with analytics, and pioneer AI/ML product features and workflows to improve user experience and platform impact.

Lead go-to-market for Mapboxs AI products: define positioning, messaging, and launch strategy; drive customer research, sales enablement, content, and cross-functional alignment to accelerate adoption of AI-powered location capabilities.

Lead document-vision research and production systems for multimodal legal evidence understanding. Define evaluation standards, frame hard problems, design and ship models, run efficacy studies and monitoring, mentor senior scientists, and advise leadership on scientific direction.

Lead and grow an applied science team building reliable, production-ready generative AI systems for legal use. Own end-to-end AI system readiness, set technical direction, perform evaluations and error analysis, partner cross-functionally to move work to scale, hire and coach staff, and represent the team externally.

Lead development and application of analytics, statistical models, and dashboards to support R&D Quality oversight. Integrate clinical, safety, lab, and operational data to identify risks, support audit/inspection readiness, enable RBQM, and provide actionable quality insights and recommendations to cross-functional partners.

Lead and grow a 9-10 engineer cross-functional team to own AI product areas (Quote Agent, Submission Triage, Product Studio). Define architecture for agentic/LLM systems, ensure engineering quality, partner with Product/Design/GT M stakeholders, and drive delivery of scalable, production AI features while fostering ownership and continuous growth.

Lead strategic vision and execution of next-generation bioinformatics technologies. Identify and evaluate emerging computational methods, translate research into production-grade pipelines and prototypes, support product roadmaps and technology transfer, and partner cross-functionally to commercialize genomic and AI-driven healthcare solutions.

Lead combined Analytics Engineering and Data Engineering teams owning the end-to-end data roadmap from ingestion to trusted metrics. Manage hiring and performance, set architecture and platform investments, enforce testing/monitoring/documentation standards, review technical decisions, and partner with product and business stakeholders to translate needs into prioritized deliverables.

Lead pricing and monetization strategy across global markets. Design pricing models and packaging, optimize discounting and payments economics, apply AI/ML analytics to drive revenue and margin, partner cross-functionally with Product, Sales, Finance, and Revenue Operations, govern pricing changes, and enable sales with pricing tools, policies, and training to improve ARR, retention, and profitability.

Analyze historical demand, occupancy, transactions and competitor pricing to optimize daily, monthly, and event pricing. Build dashboards, deliver revenue insights to leadership, and collaborate with Operations and Marketing to implement pricing and promotional strategies while maintaining data integrity.

Provide senior legal and regulatory counsel for digital health and medical device products (SaMD), guiding product lifecycle, FDA and global filings, AI-enabled features, labeling, compliance, post-market obligations, and cross-functional governance. Lead strategy, manage external counsel, and translate regulatory developments into business guidance.

Design, train, and deploy scalable ML models (generative, classification, regression). Define feature roadmaps, collaborate with engineering to implement code and APIs, adapt ML methods for distributed/GPU environments, and create evaluation/annotation programs for fine-tuning and performance measurement.

Lead product management for AI tools in software/SaaS, manage product lifecycle, drive strategic roadmap, and ensure product adoption through iterative shipping and user feedback.

Develop and scale machine learning training systems for robotics data, optimize training pipelines, and collaborate with ML researchers to enhance autonomy models.

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.

Senior leader responsible for building and scaling pre-award solution engineering capabilities to support federal sales. Oversees technical demonstrations, RFP/RFI responses, demo readiness, reusable accelerators, and cross-functional alignment with Growth and executive leadership to drive differentiated, secure solutions using modern data and AI platforms.

Lead design, development, and production deployment of ML and algorithmic solutions. Own end-to-end ML systems, support distributed production reliability, communicate tradeoffs, and apply generative AI, LLM fine-tuning, RAG, and agentic techniques to product problems.

Senior individual contributor responsible for leading pet/P&C insurance pricing model development (GLMs and ML), owning end-to-end projects, performing EDA and root-cause analysis, communicating results to stakeholders, and mentoring junior team members.

Develop, implement, and deploy scalable machine learning models for healthcare solutions. Collaborate cross-functionally to integrate models, analyze data to improve performance, ensure data quality, and stay current with ML advancements to support patient care and operational efficiency.

Lead end-to-end ML system development: data exploration, model research, training, deployment, evaluation, and MLOps. Collaborate cross-functionally to prioritize claims, improve matching, measure business impact, and own a technical workstream.

Design and scale production AI/ML systems, including autonomous agents, LLM integrations, retrieval pipelines, and virtual assistants with voice capabilities. Build and optimize models, training and deployment pipelines, APIs, and cloud-native services. Apply agent frameworks, vector databases, RAG, fine-tuning, observability, and MLOps practices. Collaborate on architecture, evaluate emerging reasoning and tool-use approaches, and mentor engineering peers.

Responsible for fine-tuning state-of-the-art LLMs, optimizing models for deployment, and driving AI architectural decisions. Collaborate with cross-functional teams to develop impactful AI products.

Build and maintain scalable ML and generative AI platforms and backend infrastructure; deploy and manage production applications; create services exposing ML/AI products; implement RAG solutions and vector databases; integrate LLM orchestration and foundation model APIs; collaborate cross-functionally and mentor teammates.