Top Remote Machine Learning Jobs in Sacramento, CA

Lead the development of innovative AI solutions, guide teams through complex challenges, and collaborate with diverse stakeholders to enhance operational effectiveness and achieve strategic objectives.

Manage AI engineering teams and client relationships, drive project deliverables, mentor staff, and uphold quality standards while leveraging advanced technologies.

Lead finance transformation engagements using Oracle Cloud ERP and EPM. Design and implement Oracle Financials and Hyperion solutions, integrate RPA/ML/analytics, ensure compliance, manage stakeholder relationships, coach teams, and drive strategic outcomes on large, cross-border projects.

Lead applied AI/ML initiatives, design and deliver production-grade software, develop secure high-quality code, troubleshoot, automate remediation, evaluate vendor architectures, champion best practices across engineering, and drive adoption of AI/ML, NLP, LLMs and streaming technologies.

The VP of Agentic Systems will lead data science research and development, focusing on AI systems to enhance cybersecurity operations, requiring strong leadership and collaboration across technical teams.

Own end-to-end analytical lifecycle to develop and optimize business, risk, and growth strategies. Monitor portfolio and macro trends, build and interpret ML-driven models, lead cross-functional launches, mentor junior analysts, and build AI-assisted workflows to improve decisioning and measurement across products and geographies.

As a Senior Data Scientist, you will lead high-complexity projects, develop ML and NLP solutions, and collaborate across teams to drive business impact through statistical modeling and data analysis.

Lead planning, deployment, tuning, and operational support of CrowdStrike Falcon's AI/ML detection and response capabilities. Implement and optimize ML models, develop automation playbooks and Falcon API integrations, troubleshoot AI-related issues, support incident response and threat hunting, and deliver customer workshops and collateral. Up to 25% travel.

The Research Engineer will collaborate with scientists to develop and validate machine learning models for speech technologies, manage scalable training systems, and design tools for accessibility to non-technical users.

Lead and architect high-value healthcare analytics engagements, build reusable analytic frameworks (DBT), partner with product and engineering, mentor analysts, ensure analytic quality, and represent Arcadia externally to drive population health and value-based care outcomes.

Lead the end-to-end demand-to-value pipeline for enterprise AI: identify high-impact use cases, make buy/build decisions, drive adoption, establish baselines and ROI, and build a team to scale business-facing AI delivery while providing credible technical evaluation of ML and generative AI.

The Staff ML Engineer will design and operate Samsara's ML platform, collaborating with teams to enhance ML features and improve safety outcomes. Responsibilities include overseeing system reliability, leading technical direction, and mentoring engineers.

Lead the development of machine learning systems for Cedar Pay's Personalization Engine, manage ML engineers, and ensure ML model effectiveness.

The AI Engineer Manager leads the Data and Analytics Engineering team in developing AI solutions, manages client accounts, analyzes data, and fosters team leadership and relationships with clients.

Intern will own and deliver a scoped engineering project on Deepgram's voice platform (ASR/TTS/LLM/API/SDK), ship reviewed code to staging/production, use AI in development workflows, improve a component measurably, and present results with documentation.

The Director of Product Management for ML Platform will own the product strategy and execution, mentor PMs, and collaborate with ML teams to enhance infrastructure and manage costs.

Lead teams building computer vision and machine learning for AI dash cameras, managing model lifecycle, coordinating with cross-functional teams, and driving AI product development.

As a Customer Success Engineer, you'll drive adoption and satisfaction for enterprise customers using Deepgram's voice AI technology, fostering strong relationships and aligning technical solutions with business objectives.

The Analytics Lead will leverage data analytics to optimize credit strategies, monitor portfolio performance, and collaborate on credit policy with stakeholders across technical and non-technical teams.

Lead planning, deployment, tuning, and operational support of CrowdStrike Falcon's AI/ML detection and response capabilities. Implement and troubleshoot AI-driven detection models, automation playbooks, API integrations, and threat-hunting for customers. Provide training, mentorship, and customer-facing collateral while optimizing detection efficacy and integrating Falcon into customers' security workflows.

Analyze malware and customer detection reports to improve machine-learning based detections, reduce false positives, reverse engineer binaries, review product detections, and support internal teams on threat detection efficacy and remediation.

Lead long-term technical strategy and execution across multiple teams, architecting and evolving foundational frontend/backend systems and platforms at massive scale. Drive AI/ML adoption, solve ambiguous, high-impact problems, remain hands-on in critical system design and implementation, and align senior leaders on roadmaps and engineering standards.

The Staff Machine Learning Engineer will lead ML initiatives, develop ML systems, collaborate with cross-functional teams, and mentor junior engineers to optimize healthcare intake workflows using advanced machine learning techniques.

Lead the design and implementation of critical Safety AI initiatives, focusing on real-time perception systems for edge devices and optimizing models for production deployment in safety-critical environments.

Lead AML model development, optimization, validation, and governance for transaction and customer screening across banking, brokerage, and lending. Build ML/statistical models, maintain vendor solutions, ensure regulatory compliance, document methodologies, produce AML dashboards, and support audits, risk assessments, and stakeholder communications.