Top Machine Learning Jobs in San Luis Obispo, CA

As a Senior Impact Analyst, you will analyze sustainability challenges, design and manage interventions, and work closely with smallholder communities, emphasizing rigorous research and collaboration.

As a Research Engineer, you'll develop and manage data systems for text-to-speech projects and enhance machine learning models using innovative strategies.

Lead a multidisciplinary team to design, deploy, and optimize ML-driven bidding systems and measurement for a nine-figure marketing budget. Drive experimentation, partner strategy, media-mix optimization, and end-to-end measurement while aligning Marketing, Analytics, Engineering, and Product to improve marketing ROI and scale performance.

The Senior Data Scientist will design and deploy time-series forecasting models, collaborate with stakeholders, and operationalize models in cloud environments, focusing on demand planning across various industries.

As an Associate Engineer in Data Science, you will leverage data analysis and machine learning to solve complex problems and develop inspiring digital products.

Senior BI Data Researcher will lead research and engineering across modern data systems: big data management, data cleaning, quality, metadata, search/discovery, information extraction, time-series and heterogeneous analytics, applied AI/ML, distributed processing, and query/storage optimization. Collaborates with research teams to build scalable tooling, ML models across diverse modalities (tabular, time series, text, audio, video), and edge-enabled architectures.

Lead and scale the Emerging Technology program, driving adoption of generative AI, ML, and data science across the company. Oversee program strategy, budget, vendor selection, compliance with SOX/FFIEC, metrics, and pilot governance. Advise senior leadership, deploy ML frameworks (TensorFlow, PyTorch, SageMaker, Azure ML), build data-driven products, and ensure secure, ethical, and enterprise-scale implementations.

Design measurement frameworks and advanced causal inference solutions for marketplace allocation and recommendation systems. Partner with Product, Engineering, and business stakeholders to translate needs into scalable data science tools, run experiments, quantify impact, and drive implementation for Netflix discovery surfaces.

Lead and support full-lifecycle data science projects (forecasting, NLP, classification/regression, optimization). Design production-ready solutions within client environments, consult with stakeholders to define ambiguous problems, communicate technical findings, and develop/teach bespoke analytics training.

This is an open talent‑community posting inviting U.S.-based candidates across multiple disciplines (software, AI/ML, XR, UX/UI, DevOps, cybersecurity, data, instructional design, etc.) to submit a resume and brief introduction. HTX Labs will retain candidate information for future contract-to-hire opportunities. Must be authorized to work in the U.S.; no visa sponsorship available. Remote-first role supporting immersive learning for Department of Defense clients.

Senior individual-contributor sales role responsible for hunting net-new consulting engagements across Data, Analytics, and AI. Build pipeline, originate opportunities, manage full sales lifecycle (prospect to signed SOW), engage senior executives, develop value propositions, and partner with technical and delivery teams. Focus on manufacturing and supply chain use cases, modern data platforms, enterprise integration, and ecosystem partners. Travel as needed to develop relationships and close deals.

Drive Midwest SLED revenue by selling analytics-driven SaaS identity and fraud solutions. Build pipeline, manage full sales cycle, develop partnerships/channels, collaborate with product, forecast accurately, and travel up to 50% to close deals and ensure customer success.

Lead product vision and execution for tDesign, an internal platform for small-molecule drug discovery. Define roadmap, translate complex AI/ML and scientific needs into intuitive UX, integrate AI agents and automated workflows, coordinate cross-functional teams, and drive adoption and product impact metrics.

Lead portfolio-level Data & AI strategy and technical governance for enterprise clients. Advise C-suite, drive architecture and modern data stacks, win high-value engagements, and scale engineering and data science teams.

The Engineering Manager will lead teams in developing and managing Blackbaud's Data & AI platform, focusing on scalability, security, and cost-efficiency.

Join Trexquant as a Global Alpha Researcher to develop trading signals, implement research, and apply machine learning for alpha discovery.

Serve as the technical lead in pre-sales for state, local, and education customers: run discovery, design POCs and workshops, deliver demos, map needs to Socure solutions, advise on fraud/risk/compliance, influence product, and mentor junior consultants.

As a Forward Deployed Machine Learning Engineer, you'll build and deploy machine learning models, enhance system performance, and collaborate with Data Science and Engineering teams for effective solutions.

Lead end-to-end deployments of AI for hotel revenue teams: integrate PMS/CRS/RMS, ship ML/optimization models and agentic workflows, validate recommendations with revenue managers, define metrics, drive adoption, and hire/mentor the forward deployed engineering team.

Lead strategy, roadmap, and lifecycle for payer analytics and automation products. Translate market, customer, regulatory, and data insights into product requirements, drive cross-functional delivery with Engineering and Data Science, support go-to-market and adoption, and measure product performance to inform investment and portfolio decisions. Build product practices and partner with stakeholders across sales, customer success, clinical, actuarial, and executive teams.

Lead Growth Engineering architecture and implementation: build Go-based data pipelines, audit/replace martech, create experimentation infrastructure, ship full-stack Go/TypeScript features, productionize ML, review team work, and apply AI-assisted development daily.

Lead and grow a team of 5–6 product developers to deliver high-quality, reliable software. Partner with product and design, champion CI/CD, testing, observability, and provide visibility to leadership while hiring and mentoring engineers.

Lead complex enterprise sales of AI-powered SaaS solutions, build pipeline, manage 6–12 month high-six-figure deals, multi-thread across stakeholder teams, collaborate with marketing/product/customer success, and translate technical AI capabilities into business ROI.

Lead execution of Product Engineering AI and automation initiatives across photonics products. Build and deploy reusable AI/automation tools, transform engineering data into AI-ready systems, and drive cross-functional adoption to improve development, qualification, manufacturing, and reliability processes.

Design, train, and productionize underwriting ML models for real-time transaction decisions. Build feature pipelines and training datasets, run experiments, integrate models into batch/real-time systems, and monitor data and model health while collaborating with cross-functional teams.