Top Remote Machine Learning Jobs in Sacramento, CA

Manage a team of data scientists to develop fraud detection models, lead planning and collaboration with leadership, and communicate outcomes effectively while maintaining strong business intuition and technical leadership.

Design, build, and operate production ML decision systems to detect and prevent payment fraud, account takeover, identity abuse, merchant/marketplace risk, scams, and other adversarial activity. Own end-to-end production lifecycle: data contracts, low-latency inference, batch scoring, feature quality, deployment, monitoring, incident response, rollback, and feedback loops. Develop AI-assisted workflows and reusable decision capabilities while partnering with modelers, product, compliance, and operations.

Design, build, and operate production ML signal systems—ranking, retrieval, recommendations, propensity, and next-best-action—covering feature/candidate generation, serving, experimentation, monitoring, and feedback. Define signal contracts (freshness, provenance, confidence), evaluate long-term impact (trust, fairness, compliance), and partner across product, data, and risk teams to deliver reusable customer-intelligence capabilities.

Lead development and production of underwriting and credit decisioning models across Cash App Borrow and Afterpay. Own full modeling lifecycle: problem formulation, feature engineering, training, calibration, experimentation, deployment, monitoring, and iteration. Build decision frameworks, agentic engineering workflows, and collaborate with cross-functional partners to align model behavior with business and regulatory goals.

The Senior Data Scientist will analyze data to drive product strategy, optimize performance, and support product launches, collaborating with cross-functional teams.

The Senior Product Manager will oversee the strategy and development of telematics data products, manage cross-functional teams, and ensure product viability and market alignment through customer insights and technical fluency.

The Senior Staff Machine Learning Scientist will lead research initiatives in computer vision and multimodal understanding, develop novel models, and translate research into practical applications while mentoring team members.

Lead the Data + ML Platform team to design, build, and operate scalable data and MLOps infrastructure. Drive platform strategy, enable ML experimentation-to-production workflows (model registry, feature stores, drift monitoring, experiment tracking), modernize streaming and batch pipelines, and scale the team while partnering cross-functionally to deliver measurable outcomes.

The Staff Machine Learning Engineer will design and build scalable ML systems, mentor engineers, and drive AI strategy at SailPoint, focusing on AI-powered identity security solutions.

Develop ML/RL models and infrastructure for AV simulations, optimize training loops, and support project timelines in autonomous vehicle tech.

Lead and coach Agile software teams, facilitate Scrum ceremonies, manage timelines, risks, and stakeholder communication, and support delivery of AI-enabled solutions across client engagements in a distributed consulting environment.

Own vision and roadmap for an AI-powered claims decision-support and auto-adjudication platform. Lead a team of product managers and cross-functional squads, translate complex claims policies into product logic, partner with business, engineering and data science, drive delivery, adoption, and measurable business impact, and communicate strategy to senior leadership.

Lead and build the full demand generation function: inbound, outbound-assist, ABM, field, and digital. Own pipeline metrics (MQLs, SQLs, pipeline contribution), run integrated enterprise campaigns, manage marketing tech stack (CRM, MAP, intent, analytics), and align closely with Sales on ICP, messaging, and pipeline quality.

Lead delivery of advanced analytics and investigative support for federal programs. Manage multiple concurrent projects, schedules, costs, risks, personnel, vendors, and stakeholder communications to ensure quality, timely contract-aligned deliverables.

The role involves developing AI technologies for customer support at Airbnb, leveraging ML systems to enhance customer experience through innovative solutions.

The Data Science Manager will lead and mentor a team of data scientists, drive data-driven decision-making across Stripe, and collaborate with various stakeholders. Responsibilities include managing projects, recruiting, and contributing to broader data science initiatives.

Design, build, and operate production AI platform capabilities and agentic workflows. Collaborate on architecture, write production-quality backend code, mentor developers, troubleshoot production issues, and drive adoption of reusable AI frameworks, MLOps practices, and cloud-native intelligent services across a multi-tenant SaaS dental platform.

Lead vision, strategy, and roadmap for Fetch's referral growth engine. Own end-to-end referral lifecycle, build incentives, experimentation, AI-driven personalization, and cross-functional initiatives to drive MAU growth and durable network effects.

Embed with customers to discover needs, design and implement production-grade integrations (APIs, data pipelines, event-driven workflows), deploy and troubleshoot solutions, train IT teams, and drive adoption and measurable business outcomes.

Perform data collection, cleaning, validation, and analysis on large client datasets using Python, SQL, and spreadsheets. Produce actionable insights and business narratives, automate data workflows, and support text/document annotation to generate labeled data for NLP and LLM solutions. Collaborate with senior analysts and improve internal analytical processes and tool configurations.

Lead enterprise application strategy and architecture for Finance and G&A, drive high-velocity billing consolidation, embed AI/automation across core workflows, ensure SOX compliance and strong controls, and build/scale an applications team while partnering with execs and vendors to accelerate transformation.

The Enterprise Account Executive will drive revenue growth by managing complex sales cycles, closing deals with Fortune 500 companies, and understanding both technical and business needs.

The Senior Machine Learning Engineer will develop ML APIs, build data pipelines, and collaborate across teams to enhance ML models and applications.

The Machine Learning Engineer develops production ML algorithms and recommendation systems, collaborates with teams, and optimizes user experiences.

Develop and experimentally validate novel ML architectures to improve prediction and design of in‑vivo molecular interactions, extending structure‑informed generative models to causal models and integrating with deployed drug‑design workflows.