Top Machine Learning Jobs in San Luis Obispo, CA

Develop data science solutions for payments across Square and Cash App. Build AI-powered tools, ETL pipelines, dashboards, machine learning models, experiments, and cloud data systems. Partner with Product, Engineering, Finance, and Operations to improve payment success, cost efficiency, risk mitigation, and decision-making. Translate business needs into practical solutions, research questions independently, and operationalize data processes and infrastructure.

Drafts, reviews, and negotiates complex data, content, licensing, distribution, vendor, and supplier agreements. Advises internal teams on intellectual property, data and content rights, AI and machine learning use cases, privacy, regulatory compliance, and commercial disputes. Partners with Content, Sales, Marketing, Finance, and Product teams; develops policies, playbooks, and project plans; monitors evolving AI and data regulations; and provides broader corporate legal support.

Leads enterprise IoT strategy, connected-product portfolio growth, commercialization, customer engagements, partnerships, and cross-functional delivery. Oversees IoT connectivity, platforms, applications, managed services, architecture, security, budgets, vendors, and portfolio economics. Builds and leads multidisciplinary teams while driving revenue growth, profitability, adoption, operational performance, risk management, and strategic alignment across a large organization.

Lead presales strategy for Workday Adaptive Planning with large enterprise customers. Conduct executive discovery, design tailored solution strategies, deliver demonstrations, communicate value, support sales cycles, showcase AI-enabled planning capabilities, respond to RFPs, represent Workday at events, and mentor peers. The role focuses on FP&A, workforce and operational planning, forecasting, analytics, and executive engagement, with travel of up to 50%.

Provides advanced technical support for robotic systems during commissioning and 24/7 customer operations. Diagnoses hardware, software, controls, Linux, network, and automation failures; analyzes logs and telemetry; develops integrations and support workflows; leads major incidents; coordinates engineering, field service, and customer teams; manages cases and corrective actions; validates AI-assisted diagnostics; and mentors engineers while improving system reliability and recovery times.

Provides statistical leadership for Medical Affairs, real-world evidence, comparative effectiveness, HTA, and HEOR activities. Designs and analyzes observational, clinical, Phase IV, and indirect treatment comparison studies; evaluates data quality, bias, uncertainty, and applicability; supports evidence-generation strategies, reimbursement submissions, publications, and scientific communications. Collaborates with statistics, epidemiology, RWE, medical, and external scientific teams to translate complex analyses into actionable conclusions.

Performs data science projects involving statistical modeling, machine learning, forecasting, data cleaning, exploratory analysis, and AI-assisted workflows. Builds and maintains models, pipelines, reporting, and analytics-ready datasets using Python, SQL, Snowflake, and dbt. Supports validation, documentation, testing, governance, and stakeholder communication while developing proficiency in modern data science tools and deployment practices.

The Senior Business Development Representative will generate enterprise sales pipeline through account research, lead identification, outbound calls, emails, and social outreach. The role qualifies opportunities, maintains accurate Salesforce records, represents Rasa’s AI platform, collaborates with sales and marketing teams, and works toward exceeding quotas. This fully remote position requires strong communication, organization, customer empathy, autonomy, and comfort working in a fast-paced startup environment.

Own the strategy and roadmap for Constructor’s search quality and Product Discovery Engine. Drive measurable improvements in relevance, conversion, revenue per visit, and GMV across retail verticals. Partner with ML, data science, and engineering teams to productionize state-of-the-art retrieval, ranking, query understanding, personalization, and LLM capabilities. Establish evaluation frameworks, investigate quality issues, align multiple teams, and expand into chapter-wide product leadership.

Lead end-to-end delivery of strategic data science and AI solutions for AI infrastructure. Work with telemetry and experimentation at fleet scale to build, deploy, and measure predictive and prescriptive models. Partner with stakeholders, present insights, enable adoption, and promote responsible AI. Collaborate closely with data engineers and infrastructure teams to productionize scalable ML solutions.

Develop data tools, AI automations, ETL pipelines, dashboards, and machine learning models for payments. Analyze experiments, optimize payment performance and costs, mitigate risk, maintain data systems and cloud infrastructure, and translate business needs into actionable solutions while partnering with Product, Engineering, Finance, and Operations.

Owns operations for Optain’s nationwide network of contracted optometrists and ophthalmologists. Responsibilities include creating provider policies and SOPs, running quality and performance programs, modeling capacity, managing recruitment, handling complaints and urgent findings workflows, and preparing governance decisions for the Medical Director. The role partners with Product and Engineering to automate network processes and requires experience in healthcare operations, clinician networks, clinical quality, credentialing, and multistate licensing.

The AI Engineer will build data pipelines and improve ML systems for reliability in production. Responsibilities include schema design, data infrastructure, and model evaluation, ensuring high-quality outputs and integration with product workflows.

Lead the technical direction of Quora’s recommendation ecosystem, including feed retrieval, ranking, re-ranking, optimization, data pipelines, feature engineering, model training, and production integration. Drive measurable improvements through experimentation, apply generative AI, mentor engineers, and partner across product, data science, and infrastructure teams.

Leads delivery of large-scale AWS and digital transformation programs, overseeing planning, execution, reporting, risk mitigation, quality, and customer outcomes. Manages multi-functional teams of business analysts and engineers, develops product and service roadmaps, drives continuous improvement, and resolves customer issues. The role also involves people management, recruiting, coaching, business development, stakeholder communication, and aligning program portfolios with organizational strategy.

Manage a portfolio of advertisers on the Adflow commerce media platform, building relationships, monitoring budgets and campaign performance, presenting business reviews, coordinating onboarding, recommending optimization strategies, and identifying revenue-growth opportunities. The role serves as the primary client contact, collaborates with internal campaign, media operations, creative, and finance teams, and uses performance marketing expertise and analytics to drive advertiser success and long-term partnerships.

Manage a portfolio of advertisers on the Adflow commerce media platform. Responsibilities include client onboarding, campaign coordination, budget and revenue pacing, performance reporting, business reviews, strategic recommendations, optimization feedback, and identifying opportunities to grow advertising spend and channel distribution. The role serves as the primary client contact while collaborating with business development, campaign strategy, creative, media operations, and finance teams.

Provides technical leadership for architecture and evolution of large-scale distributed data platforms supporting Azure network telemetry. Designs streaming and batch systems, establishes reusable engineering patterns, drives cross-team technical strategy, and owns capabilities from design through production operations. Ensures scalability, reliability, security, performance, data quality, and operational excellence while mentoring engineers and influencing technical leaders. The role also involves architectural reviews, dependency management, risk reduction, and applying AI or machine learning approaches to operational systems.

Serve as the primary business intelligence and analytics partner for Governance, Risk & Assurance and the General Counsel Strategy Office. Analyze complex datasets, build dashboards and data models, support data governance and risk initiatives, identify automation and AI opportunities, and translate technical findings into business recommendations. Collaborate across enterprise functions, provide reporting and technology guidance, evaluate AI solutions, and drive adoption of data-informed practices.

Design, develop, and operate scalable software platforms and automation for Azure network qualification infrastructure. Build tools for device provisioning, configuration, lifecycle management, testing, telemetry, and health validation. Develop AI-powered agents for troubleshooting, root-cause analysis, and engineering productivity. Create reliable distributed systems with observability, diagnostics, automated recovery, and scalability while collaborating across software and network engineering teams.

Leads global Customer Success for enterprise cybersecurity SaaS customers, owning onboarding, adoption, retention, renewals, expansion, advocacy, and customer satisfaction. Develops scalable CS strategies, support processes, KPIs, AI-driven workflows, adoption programs, and executive engagement frameworks. Partners with Sales, Product, Engineering, Finance, and Marketing while managing teams across the US and India. Drives GRR, NRR, product adoption, customer value realization, and referenceability.

Develop marketplace intelligence, forecasting, ranking, recommendation, personalization, and experimentation models for Airbnb’s search and marketplace products. Partner with product and engineering teams to launch AI-driven improvements, build scalable modeling pipelines, evaluate product changes, and guide technical direction. The role requires causal inference, machine learning, strong SQL and Python or R skills, cross-functional communication, and autonomous leadership of data science roadmaps.

Develop machine learning and statistical models to identify, measure, and manage credit and fraud risk. Partner with stakeholders to translate requirements into scalable solutions, analyze large application and transaction datasets, deploy end-to-end models, and improve risk decision-making. The role requires advanced Python or R and SQL skills, expertise in fraud and underwriting models, model deployment, statistical methods, and mentoring junior data scientists.

Leads marketing and sales analytics strategy, architecture, and measurement. Builds data models, pipelines, machine learning datasets, attribution and incrementality models, and revenue-performance analyses. Advises leaders on investments, tools, account prioritization, and funnel economics. Establishes data, metric, testing, and privacy standards; partners with Marketing, Sales, Finance, Revenue Operations, Data Engineering, and IT; plans roadmaps; presents recommendations to executives; and mentors analysts and engineers.

Own product outcomes for an AI-native cloud infrastructure platform. Conduct customer discovery, frame problems, prioritize opportunities, prototype solutions, analyze product and business data, and collaborate with Design, Engineering, Sales, Customer Success, and Marketing. The role requires enterprise B2B product judgment, technical fluency across cloud infrastructure and FinOps, strong commercial awareness, AI-assisted workflows, outcome measurement, and end-to-end ownership from strategy through iteration.