Top Machine Learning Jobs in Sacramento, CA

The Engineering Manager will lead a team in developing a Dispatch Optimization platform, focusing on data science, ML engineering, and operational efficiency, while fostering talent and ensuring project delivery.

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.

Provide technical pre-sales support for SailPoint, managing proof-of-concept processes, architecting solutions, and developing custom code for identity management.

As Principal Product Manager for the Agentic Platform, you will set the vision and strategy for AI infrastructure, drive product development, and facilitate adoption across teams.

Manage a team of ML engineers to build and optimize Affirm's economic decisioning engine using advanced ML techniques. Collaborate across teams, provide technical leadership, and mentor engineers while driving a cohesive long-term ML strategy.

The Machine Learning Engineer will design, build, and maintain production machine learning systems, focusing on scalability, reliability, and integration with existing products. Responsibilities include developing ML pipelines, establishing ML Ops best practices, and collaborating on product capabilities.

Lead development of a greenfield data product by partnering with customers and product teams to build analytics and models (simulation, Bayesian networks, optimization, ML). Maintain existing analytics, improve predictive churn models, and translate customer needs into production-grade SQL/dbt pipelines, dashboards, and data-driven product features.

As a Customer Service Representative, you'll manage inbound customer calls, provide exceptional service, handle payment processing, and maintain customer accounts post-training.

The Strategic MSP/MSSP Account Executive will identify and develop partnerships, create strategic plans, and drive revenue growth by engaging with prospective MSP/MSSP partners while collaborating internally to optimize sales strategies and maintain relationships.

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

The Enterprise Account Executive will manage the complete sales cycle, build relationships with senior leaders, and drive platform adoption within data-intensive organizations.

As a Technical Content Writer, you will create and manage technical documentation for Runpod's GPU cloud platform, collaborating with various teams to ensure clarity and engagement while staying updated on AI trends.

The Senior Manager of Product Management will oversee the integration of AI and data science models into planning applications, ensuring user trust and model accuracy while managing stakeholder communication and adoption.

The role involves demand forecasting for PC products, data analysis and reporting, cross-functional collaboration, process improvement, and AI integration.

Agap Technologies, Inc. offers online Machine Learning training with real-time instruction, immediate support, interview training, and OPT guidance for enrolled trainees.

The Staff Research Scientist will conduct AI research, innovate in LLM and information retrieval, and collaborate with research teams.

Lead the machine learning strategy, design scalable ML systems, drive MLOps, mentor engineers, and comply with AI governance.

The role involves building and optimizing a machine learning and simulation platform, supporting MLOps, model deployment, and infrastructure modernization, while mentoring engineers.

In this role, you will lead AI personalization initiatives, develop AI/ML models for user experience, collaborate across teams, and ensure rigorous development practices.

Lead machine learning initiatives to enhance underwriting model accuracy. Design and implement advanced training strategies and optimize workflows. Mentor engineers and influence modeling strategy.

The engineer will build and operate AI/ML infrastructure, managing services on AWS and bare metal, using tools like Kubernetes and Terraform.

As an ML Ops Infrastructure Engineer, you will design CI/CD pipelines for ML, maintain deployment systems, and implement monitoring while collaborating with research teams to ensure model quality and performance.

As a Systems Architect, you'll define and drive the infrastructure architecture for AI/ML workloads, design multi-cloud strategies, manage compute orchestration and storage systems, and lead capacity planning, while also collaborating with engineering leadership.

As a Staff Machine Learning Engineer, you will design AI products on Edge devices, optimize ML model performance, and work with large-scale datasets, collaborating across teams to deliver impactful solutions.