Top Machine Learning Jobs in Sacramento, CA

Lead and scale Vibrant's data science, ML, and AI function: set strategy and governance, oversee applied research and production ML (especially NLP), ensure HIPAA-compliant deployments, partner with execs and engineering, recruit and mentor teams, and deliver measurable outcomes for crisis services and enterprise initiatives.

The Senior Clinical Informatics Sales Specialist drives adoption of informatics products by providing technical expertise, engaging with healthcare leaders, and developing sales strategies for genomic data analytics.

Lead end-to-end research applying advanced ML/DL (transformers, GNNs, RL, ensembles) to generate alpha across digital asset markets, build production-grade pipelines, prevent leakage/overfitting, analyze microstructure and on-chain data, and mentor junior researchers.

The AI Sales Executive drives new business growth and expands client relationships by selling AI-driven solutions for engineering and manufacturing sectors, managing the full sales cycle with a consultative approach.

Own and implement end-to-end product features across the stack (React/TypeScript front end, Ruby on Rails backend, relational DBs, GCP infra). Design APIs and data models, ensure performance and reliability, integrate AI/LLM-powered features, collaborate with product/design/clinical teams, perform code reviews, and mentor junior engineers.

Own Oscilar's AML product suite (transaction monitoring, KYC/KYB, screening, case management, SAR filing, AI agents). Define detection rules, model calibration, data strategy, and defensible audit trails. Collaborate with engineers and compliance, use AI across discovery/design/analysis, deliver PRDs, validate models, and ship production features.

Lead high-impact strategy and BizOps workstreams including M&A diligence, investor relations, new-market expansion, and cross-market operations. Frame ambiguous, board-level problems, build analysis and recommendations, align stakeholders, and own execution end-to-end while leveraging AI and automation.

Build and maintain backend services and infrastructure for ML and generative AI features. Develop scalable, resilient, high-performance Python services (async frameworks, streaming), deploy to Kubernetes, integrate RAG and LLM orchestration, instrument LLM observability, and collaborate cross-functionally to deliver production-ready AI products.

Build and maintain scalable ML and generative AI platforms and backend infrastructure; deploy and manage production applications; create services exposing ML/AI products; implement RAG solutions and vector databases; integrate LLM orchestration and foundation model APIs; collaborate cross-functionally and mentor teammates.

Design and productionize LLM/NLP pipelines for regulation parsing and semantic search (RAG). Build forecasting, risk-scoring, and optimization models for supply chain. Implement MLOps: containerized deployments (Docker/Kubernetes), pipeline orchestration (Kubeflow/MLflow), inference optimization, and monitoring with retraining loops. Apply transformer models and prompt engineering for domain-specific tasks and convert natural language requirements into executable rule formats.

Lead development and refinement of machine learning pricing models (especially reinforcement learning) for Airbnb hosts. Collaborate with data scientists, product, and engineers to design, test, integrate, and monitor models, analyze performance, and prioritize projects to improve host outcomes.

This is a general talent-community application inviting candidates across many functions to submit resumes. Recruiting will review and retain applications for future openings; candidates should highlight experience, accomplishments, and interests for potential remote roles.

Design, develop, and deploy AI-driven Salesforce applications, autonomous agents, intelligent workflows, and decision-support capabilities. Implement Agentforce, Einstein AI, Prompt Builder, Data Cloud, LLMs, RAG, and integrations with enterprise systems. Build human-in-the-loop experiences, AI-native UX, analytics dashboards, and scalable architectures while ensuring security, governance, and Agile/DevSecOps practices.

Develop, implement, and deploy scalable machine learning models for healthcare solutions. Collaborate cross-functionally to integrate models, analyze data to improve performance, ensure data quality, and stay current with ML advancements to support patient care and operational efficiency.

Conduct ML research for query understanding, ranking, clustering, and AI-powered search. Prototype and productionize algorithms, define data and evaluation requirements, design scalable systems, collaborate with engineers, run experiments, and publish patents/papers to integrate state-of-the-art ML into Yahoo Search products.

This role involves leading strategic planning, product innovation, and cross-functional collaboration to enhance pharmacy analytics and drive growth initiatives for CVS Health.

Lead design, training, fine-tuning, and deployment of ML and generative models (LLMs, diffusion). Build scalable MLOps pipelines, vectorization and data ingestion, integrate models into microservices for low-latency inference, implement evaluation/alignment/bias-mitigation, optimize models (quantization, distillation), and mentor engineers while influencing the AI product roadmap.

As Director of AI/ML, lead the ML organization, set technical vision, mentor a high-performing team, and contribute to model development and production deployment.

The Director of Data Sciences leads a team in strategic initiatives, drives machine learning and AI solutions, and manages resources to enhance data-driven decision making across the business unit.

The AI & Data Science Director will lead AI strategies, foster technical leadership, support team development, and integrate generative AI into products.

Design, build, and deploy high-throughput ML and LLM-powered personalization and agentic systems at consumer scale. Process petabyte-scale data, optimize real-time inference, implement resilient fallback paths, and balance latency, cost, and model quality while collaborating across engineering and product teams.

Lead development of an AI-enabled Ethereum Layer 2 platform: build front-end and back-end systems, deploy and optimize AI models, create data pipelines, collaborate on model training, and contribute to product innovation and other company projects.

Sell HiddenLayer's AI security platform to federal agencies by developing account strategies, driving pipeline and revenue, leading technical and executive engagements, navigating federal acquisition and contracting, coordinating cross-functional teams, and supporting adoption, expansion, and renewals across the Intelligence Community, DoD, DHS, and civilian agencies.

Lead the engineering vision for threat detection, architect scalable systems, foster community intelligence, and create a culture of technical excellence and innovation.

The Manager of RevOps/Yield analyzes patterns and data to optimize ad operations, manage vendor relationships, and oversee a remote team for revenue generation.