Top Senior Machine Learning Jobs in Sacramento, CA

Leads and develops a fraud analyst team responsible for investigating emerging threats, responding to incidents, and improving fraud-risk strategies. Owns investigative standards, playbooks, workflows, and tools while serving as an escalation resource for complex cases. Partners with Data Science, Customer Success, Product, Engineering, and business leaders to convert fraud insights into scalable signals, model improvements, and better customer outcomes. Supports customer conversations as a fraud subject-matter expert and coaches analysts on communicating risk decisions.

Design, scale, and optimize ClickUp's search infrastructure using OpenSearch/Elasticsearch. Improve relevance, speed, and real-time indexing, build vector search capabilities, create evaluation frameworks, and collaborate with AI/backend/product teams to integrate and troubleshoot search at scale.

Prototype and develop generative AI applications for business software, including automated model evaluation, synthetic video, and consistent image and brand asset generation. Own projects from experimentation through product delivery, combining system architecture, quantitative reasoning, product judgment, and creative LLM application development.

Lead analytics for client engagements across data onboarding, study planning, predictive modeling, production deployment, and ongoing optimization. Develop models for audience targeting, segmentation, propensity scoring, and campaign optimization, primarily for commercial pharmaceutical applications. Partner with business, analytics, and IT stakeholders, lead technical workshops, present findings to senior audiences, and manage client relationships. Build machine learning pipelines using Python, SQL, and cloud technologies, while contributing client insights to internal product development.

Develop and maintain Power BI reports, dashboards, visualizations, semantic models, and analytics solutions. Translate business requirements into scalable technical solutions, optimize queries and data models, ensure reporting accuracy and performance, and support data governance. Serve as the primary liaison for business users, provide training and troubleshooting, manage tickets, and collaborate with Data and QA teams. The role also advances AI and machine learning capabilities, mentors colleagues, and contributes to automation, documentation, and code reviews.

Conduct applied AI and machine learning research focused on multimodal data, foundation models, agents, evaluation, and data enrichment. Monitor research trends, prototype emerging techniques, design experiments, validate opportunities, and translate findings into briefs and recommendations. Partner with product and engineering teams to guide data strategy, training corpus generation, and longer-term opportunity prioritization.

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.

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.

Own the clinical infrastructure and program portfolio powering Arine’s medication management platform. Evolve the clinical recommendation engine, expand data inputs, standardize program configuration, and create repeatable frameworks for launching and scaling clinical programs. Partner with clinical, engineering, data science, implementation, and customer success teams to translate needs into requirements, improve onboarding, maintain regulatory alignment, and prioritize work using clinical safety, user value, and business impact.

Leads engineering for one or more product-domain teams, partnering with Engineering Managers, Product, Data Science, Analytics, and Insurance stakeholders. Responsibilities include setting technical strategy and roadmaps, coaching engineers, driving cross-team initiatives, contributing code, leading incident response and resiliency improvements, and establishing engineering standards. Requires strong Ruby on Rails expertise, Rust familiarity, software leadership experience, and excellent communication skills.

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.

Lead the demand generation function by translating go-to-market priorities into segmented campaigns across email, search, social, content, webinars, and events. Own HubSpot automation, Salesforce integration, lead scoring, funnel analytics, marketing-sourced pipeline, budgets, and agency performance. Collaborate with Sales and Commercial Operations to improve lead handoffs and conversion. Apply AI and automation to increase execution efficiency while coaching team members and building the future demand generation team.

Leads new business development, account growth, commercial discussions, client relationships, and sales operations for AI and GenAI data solutions. Partners with engineering, delivery, and customer success teams to understand frontier lab needs, structure projects, close opportunities, and expand client accounts. Requires quota-based technology sales experience, startup experience, STEM education, and strong AI/ML market knowledge.

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.

Lead the design, productionization, and operation of machine learning and agentic AI capabilities. Partner with product engineering, shape AI/ML architecture, build evaluation systems and data pipelines, and develop reliable MLOps tooling. Champion responsible AI, safety, latency, cost, and error handling. Serve as a technical resource for engineers, influence direction, mentor others, and occasionally explain AI functionality to customers or customer-facing teams.

Lead the vision, strategy, and evolution of LTK’s creator experience and commerce products. Define creator workflows, identify AI-powered opportunities, analyze behavioral data, establish outcome metrics, and drive experimentation to improve engagement, retention, earnings, and product quality. Collaborate across Product, Engineering, Design, Data, and Creator Success while influencing senior stakeholders and guiding complex, multi-quarter initiatives.

Build product enablement for global go-to-market teams across AI Agents, APIs, and Creative products. Responsibilities include preparing launch workshops, competitive training, product certifications, onboarding and everboarding content, hands-on demos, role-play simulations, practice environments, and performance measurement. The role partners with product marketing, engineering, research, and enablement teams while using ElevenLabs’ AI technology to create training experiences.

Owns CSL Plasma’s target-state business architecture, capability models, value streams, architecture decisions, integration standards, and technology roadmaps. Translates business strategy and regulatory requirements into architecture blueprints across digital products, while governing AI, automation, data, and integration patterns. Partners with product, engineering, enterprise architecture, security, privacy, and compliance teams to drive committed designs, architectural consistency, and migration sequencing across a complex regulated environment.

Own end-to-end client relationships for a book of B2B SaaS customers: drive adoption, engagement, retention, and expansion of AI-powered contract drafting tools. Lead onboarding, training, large-scale rollouts, and translate customer feedback into product improvements while designing scalable CS processes and tracking health metrics to demonstrate value.

Define the vision, strategy, and roadmap for AI-powered products. Lead use-case evaluation, requirements, experimentation, development, deployment, adoption, and continuous improvement across Generative AI, LLM, RAG, and agentic solutions. Collaborate with engineering, data science, design, and business stakeholders; establish success metrics; manage AI risks; and communicate product value, progress, and strategy to leadership and clients.

Lead enterprise data and AI architecture across marketing, customer engagement, digital, sales, and analytics. Design scalable cloud data platforms, reusable data products, semantic models, real-time and batch architectures, governed AI capabilities, machine learning systems, generative AI, agents, recommendations, and personalization. Establish standards for governance, security, privacy, quality, lineage, and observability. Provide technical direction, lead architecture reviews and roadmaps, partner with engineering and data science teams, and mentor architects and engineers.

Lead enterprise security operations, resilience, incident response, threat intelligence, cloud security, IAM, and risk management. Serve as deputy to the CISO and primary incident commander while advising executives on cyber risk. Build and scale multidisciplinary security teams, modernize cloud-native defenses, embed security-by-design across products and AI/ML systems, and establish metrics-driven governance, automation, regulatory alignment, and business-focused security strategies.

Senior Product Designer responsible for creating high-craft, 0-to-1 AI recruiting and talent product experiences. The role involves visual and interaction design, rapid iteration, prototyping, design-system development, production-ready delivery, and experimentation with generative AI. Candidates should have strong Figma expertise, exceptional visual design skills, experience shipping SaaS, enterprise, or AI products, and a portfolio demonstrating creative range and execution.

Leads data engineering teams while designing and optimizing scalable batch and real-time data pipelines on cloud platforms. Responsibilities include developing PySpark and Spark workflows, orchestrating Airflow DAGs, managing cloud infrastructure, implementing CI/CD, improving data quality and performance, and mentoring engineers. The role collaborates with clients, product, architecture, and program management teams, while applying generative AI and DevOps practices to improve engineering productivity and operational efficiency.

Design the full Search experience across organic and sponsored results, including typeahead, ranking, filters, empty states, and monetization. Establish design principles and components, partner with product, research, data science, and ML engineering, and use experimentation to improve engagement, relevance, and revenue. The role requires substantial search or discovery design experience, strong product craft, consumer instincts, and comfort designing alongside AI and monetization teams.