Top Remote Machine Learning Jobs in Sacramento, CA

As a Staff Applied ML Scientist, you will develop and maintain fraud detection models, conduct research on fraud types, and collaborate across teams to drive product development and real-time decision-making.

As a Senior Applied ML Scientist, you'll develop fraud detection models, research new fraud types, and write production code while collaborating across teams to enhance SentiLink's identity verification solutions.

The Principal AI/ML Engineer will develop machine learning models for campaign optimization in AdTech, collaborating across engineering and product teams to enhance advertising capabilities.

The Enterprise Account Executive drives revenue through high-value contracts, managing complex sales processes and relationships with executive stakeholders in financial services.

As Co-Founder & CEO, you will define strategy, lead customer development, drive product iterations, raise capital, and build the founding team for InfluTracker, an AI content intelligence venture.

Design and implement machine learning models to solve business problems, analyze data for insights, and optimize model performance.

Design, deploy, and maintain end-to-end ML-driven risk solutions at scale to detect and prevent fraud, abuse, and credit risk. Lead technical decisions, build ML tooling and processes, apply state-of-the-art models and third-party data, investigate emerging risk patterns, and collaborate with platform and cross-functional teams to ensure reliable real-time model operation.

Design, deploy, and maintain end-to-end ML risk solutions at scale to detect and prevent fraud, merchant risk, and credit loss. Partner with cross-functional teams, lead technical decisions, build ML tooling, monitor models in production, and investigate emerging abuse patterns to improve detection and decisioning.

Lead design, build, and scale backend and frontend components for Pearl's clinical product suite. Own engineering architecture and deployments, integrate systems with ML/computer vision pipelines, use AI-assisted development tools to accelerate delivery, improve engineering velocity and quality, and mentor teammates in AI-augmented workflows.

The Director of Artificial Intelligence will define, lead, and implement AI strategies, managing R&D, building teams, and ensuring ethical AI use to drive business outcomes.

Lead Data Science initiatives, build AI/ML solutions, and mentor teams in a collaborative environment, driving innovation in a leading construction equipment venture.

The Director of Computer Vision will lead technical vision, research, and execution in developing scalable AI-driven computer vision solutions, managing teams, and enhancing performance metrics.

The Senior Product Manager will set product direction, own the development lifecycle, collaborate with teams, and ensure high-quality outputs. This role requires strong opinions on product quality and customer insights.

Lead the Decision Science function, designing ML models, overseeing experimentation frameworks, and ensuring model adoption across the company, driving operational and commercial improvements.

The Senior Developer Relations Manager will engage with developer ecosystems in agriscience, driving the adoption of NVIDIA technologies through technical guidance, collaboration, and strategic advocacy. Responsibilities include advising on resources, onboarding partners, monitoring ecosystems, and collaborating across functions to promote successful integrations.

The Principal AI/ML Researcher/Engineer will lead research and development of reasoning, planning, and decision-making systems, integrating multi-agent coordination with reinforcement learning to enhance Airbnb's AI capabilities for personalized experiences.

Lead design and delivery of a unified, real-time billing platform that embeds AI/ML to automate reconciliations, detect anomalies, enable predictive insights, and create autonomous finance workflows across global billing operations.

Own end-to-end lifecycle for AI features: define requirements, run model evaluation and experimentation, maintain capability-level AI roadmap, apply responsible AI principles, measure success metrics, iterate with engineering, UX, security, and go-to-market to deliver customer-ready AI capabilities.

Design, build, and maintain scalable AI/ML pipelines for data processing, model training, and deployment. Collaborate with data scientists and engineers to implement and optimize AI solutions, troubleshoot pipeline issues, document best practices, and develop MVP code to transition into production-ready systems.

Lead product marketing for ExtraHop's Agentic SOC, shaping category narrative, translating customer and partner insights into launches, sales enablement, content, and go-to-market programs while engaging security practitioners, product, and partners to drive adoption of AI-powered security operations.

Architect and deliver AI-driven documentation systems (TMS/CMS/automation) for regulated technical publications. Design and deploy ML/NLP/Generative AI tools, optimize translation memory, support DITA/XML workflows and FrameMaker templates, build Python scripts for publishing and content reuse, and evaluate documentation workflows to improve localization, quality, and analytics.

Lead and scale engineering teams building Protect, a real-time multi-signal fraud detection platform. Set technical strategy, develop managers and senior engineers, deliver distributed systems and APIs, improve architecture, observability, reliability, and developer productivity while partnering with Product, Research, Security, and exec stakeholders.

Design, build, and deploy AI-driven documentation and localization systems (TMS/CMS), improve translation memory and automation, support DITA/XML workflows, develop Python scripts for publishing, and implement generative AI/NLP solutions within a regulated life-sciences environment.

Lead client-facing Data & Analytics engagements across pre-sales, architecture, and delivery. Define strategy, roadmaps, solution designs, and SOWs for modern data platforms, pipelines, governance, analytics, and AI enablement. Drive practice development, create reusable IP, mentor teams, and ensure quality delivery and strong business outcomes.

As a Senior Machine Learning Engineer, you'll design and develop workflows utilizing vision-language models, manage data pipelines, and collaborate with multiple teams to enhance model accuracy and efficiency.