Top Remote Machine Learning Jobs in Sacramento, CA

Manage the implementation of iQueue for Operating Rooms, collaborating with healthcare clients to optimize workflows and ensure successful adoption of the product.

The Head of Product will drive strategic initiatives, lead product development, partner with executives, and ensure alignment with business objectives in the fintech industry.

The role involves researching, developing, and implementing AI solutions, optimizing models, integrating AI into workflows, and collaborating with teams to enhance business efficiency.

Develop and implement AI solutions, optimize models, preprocess data, integrate AI into workflows, and collaborate with cross-functional teams.

The Technical Product Manager will develop and manage the cloud infrastructure for AI, collaborating across teams to enhance AI solutions and service offerings.

As an AI Applications Engineer, you will bridge AI research and implementation, driving experiments, building infrastructure, and releasing products to improve user experience and metrics.

Join Invoca's Talent Community to stay updated on job openings and to explore exciting career opportunities across various departments.

The Senior AI Engineer at RegScale designs and operates AI systems, ensuring reliability and performance while overseeing the data pipeline and compliance integration, alongside improving AI capabilities across the engineering organization.

Manage the development and implementation of Evio Compass, an analytic product identifying patient risks, while guiding cross-functional teams to drive customer success and enhance ML/AI product features.

The Senior Display Media Account Manager develops and executes digital media strategies, focusing primarily on Amazon DSP, while fostering client relationships, providing analytics, and driving business growth for clients.

The Product Manager, Growth connects product teams with market insights, conducts customer interviews, organizes feedback, and supports go-to-market strategies.

Define and execute Americas logistics and warehousing strategy; lead multi-site DC operations, inbound/outbound logistics, carrier management, trade compliance/imports, P&L oversight, WMS/TMS/ERP optimization, and AI/automation adoption. Requires cross-regional enablement and ~25-40% travel.

Lead strategy and roadmaps for platform offerings that support robotics and autonomous systems. Drive customer discovery, define requirements and metrics, coordinate cross-functional execution, ensure production readiness, and lead adoption, rollout, and stakeholder communication for platform capabilities.

Lead partner marketing with consulting and systems integrators to drive joint GTM plans, co-marketing programs, repeatable partner collateral, customer stories, partner communications, and measurable pipeline growth.

The role involves defining the vision and strategy of the Outreach AI Platform, prioritizing the roadmap, collaborating with engineering and data science teams, and engaging with customers to refine AI strategies.

The CX Outbound Solution Engineer designs and deploys outbound contact center solutions, focusing on operational efficiency and customer engagement. They work with sales to align solutions with customer needs and lead pilot implementations with a strong grasp of outbound regulations and technologies.

Lead and mentor a software engineering team building the intake and authentication systems that feed a global Item Master. Partner with Product and AI/ML to integrate computer vision, automated tagging, and robotics into warehouse workflows. Own architecture, scalability, backend services, database design, and vendor/hardware integrations while driving agile delivery and operational OKRs.

Own the upper-funnel global DTC experience for ouraring.com, define roadmap and run high-velocity A/B experimentation, ship AI-powered personalization, partner cross-functionally to drive conversion, revenue, and localized market experiences.

Lead vision, strategy, and execution for Alkami's marketing products. Define roadmap, embed AI-driven personalization and audience intelligence, partner cross-functionally to drive adoption and revenue, recruit and develop product managers, and deliver scalable SaaS marketing and analytics solutions for financial institutions.

Lead cross-functional teams to design, build, and maintain technical applications and data services for health services research, AI research, and precision medicine. Gather customer requirements, define product roadmaps, oversee build/test/validate/iterate cycles, measure outcomes, and manage analytic products and data architecture in cloud/big-data environments.

Senior leader driving enterprise transformation through end-to-end M&A integration and an Integration Management Office, building AI- and analytics-driven offerings, leading VP-level client delivery, structuring executive decisions, and communicating recommendations to C-level stakeholders.

Design and lead end-to-end AI solution architectures, ensuring scalability, security, and compliance. Translate business and regulatory requirements into technical designs, evaluate tools/platforms, document architecture standards, coordinate technical teams, and support deployment and ongoing improvements.

Lead product analytics to improve user growth, engagement, retention, and revenue. Design and analyze A/B and multivariate experiments, perform funnel/cohort analyses, maintain KPIs and dashboards, ensure event tracking, leverage ML and AI tools for advanced analyses, and translate insights into product recommendations across cross-functional teams.

Lead product vision and roadmaps for a global Library GovTech product. Define AI-enabled features, prioritize requirements, oversee product lifecycle, collaborate with engineering, design, and commercial teams, run customer research, manage launches, and use data to drive decisions and mitigate risks.

Lead complex, cross-functional AI programs end-to-end: translate strategy into integrated plans, drive multi-team execution, mitigate risks (data, model, compliance), apply ML lifecycle practices, use Agile/kanban methods, manage budgets/vendors, communicate to senior stakeholders, and mentor other program managers to improve AI program standards.