Top Machine Learning Jobs in Sacramento, CA

Leads data engineering and data science teams, setting strategy and delivering scalable pipelines, data architecture, models, analytics infrastructure, and data governance. Partners with product, analytics, and business stakeholders to prioritize initiatives, assess upstream changes, maintain data quality, and support Snowflake-based warehousing. This hands-on leadership role includes mentoring staff, contributing to technical codebases, and advancing data science and engineering solutions.

Develop and productionize machine learning models and predictive analytics using Python, Databricks, PySpark, SQL, and Delta Lake. Build scalable data science workflows, resolve healthcare data quality and entity-resolution issues, and apply Master Data Management practices. Partner with engineering, product, analytics, and business teams to deliver governed, HIPAA-compliant solutions. Perform exploratory analysis, feature engineering, model evaluation, deployment, documentation, and data lineage management for healthcare and member engagement initiatives.

Leads complex AI client projects from requirements gathering through delivery, serving as the primary client contact and coordinating Sales, Operations, Product, and Engineering. Responsibilities include defining scopes and delivery plans, managing risks, quality, timelines, budgets, profitability, and KPIs, resolving execution challenges, and improving scalable processes for AI project delivery.

Leads technical pre-sales and foundational implementation engagements for SailPoint SaaS solutions. Discovers customer requirements, maps them to product capabilities, delivers proof-of-value implementations, explains architecture and best practices, and collaborates with sales, product, services, and customer success teams. Develops AI and agentic technology solutions for demonstrations and customer problems, while serving as a technical and consultative advisor to customers, partners, and colleagues.

Lead technical customer engagements for strategic accounts, supporting sales, solution design, foundational implementations, and proof-of-value deployments. Discover requirements, map them to SailPoint solutions, educate customers on architecture and best practices, collaborate across sales, product, professional services, and customer success, and develop AI- and agentic-technology solutions for demonstrations and customer outcomes.

Forward Deployed Engineers support sales and customer engagements by discovering requirements, designing and implementing foundational SaaS solutions, delivering proof-of-value implementations, and educating customers on architecture and best practices. They collaborate with sales, product, professional services, and customer success teams; use AI and agentic technologies to solve customer problems; lead technical engagements; document requirements; and develop reusable demonstration solutions. The role may require up to 15% travel.

Leads a data science team focused on customer intelligence and personalization across digital products, apps, newsletters, and marketing channels. Develops lifetime value, segmentation, retention, recommendation, attribution, forecasting, and engagement models. Owns product funnel analytics and experimentation, including A/B testing and causal inference. Partners with Product, Marketing, Editorial, Data Operations, and Engineering to translate customer behavior into product improvements, measurable growth, and scalable data capabilities.

Develops and productionizes deep learning and machine learning perception models for robotics and recycling sortation. Responsibilities include experimenting with neural network architectures, designing computer vision solutions, conducting statistical experiments, deploying successful models, collaborating with data, modeling, and cloud infrastructure teams, and improving ML infrastructure.

Analyze and characterize conversational audio data, identify underrepresented areas, and build active-learning and human-in-the-loop workflows. Develop representative benchmarks, automate model adaptation, and create reusable data analysis and scoring systems. Partner with research, engineering, and data teams to run experiments, improve models, organize data, and translate complex findings into measurable product improvements.

Lead Sardine’s fraud product portfolio, setting vision and roadmap across device intelligence, behavioral biometrics, and machine learning. Manage product managers and partner with engineering, data science, risk operations, marketing, and sales. Drive fraud detection performance, reduce false positives and customer friction, monitor emerging threats, and scale zero-to-one products into enterprise-ready solutions for payment and fraud-prevention customers.

Leads the enterprise data strategy, builds and scales the Data & Analytics team, and oversees data warehouse modernization, migration, governance, KPI standardization, and data quality. Partners with executives and cross-functional teams to convert data into actionable insights, operational improvements, predictive analytics, and AI-enabled workflows. The role requires hands-on Python, SQL, cloud, machine learning, and ETL expertise, plus strong leadership and communication skills.

Leads a data science team and personally drives analyses, experimentation, and product analytics to identify patient experience improvements. Partners with Product, Engineering, Research, and Data Engineering teams to develop product features, evaluate business and product performance, guide product planning, and translate statistical findings into actionable recommendations. Manages and develops analytical talent while applying data storytelling, A/B testing, marketplace metrics, and retention, conversion, engagement, and churn analysis.

Lead the In-Vehicle Experience team at Samsara, focusing on transforming in-cab cameras into intelligent companions. Collaborate with engineering, prioritize features, and ensure client interactions highlight trust and connection. Conduct customer research and integrate AI and ML into product features.

Leads Lyra Health’s AI/ML engineering roadmap, scales and mentors machine learning teams, and drives production-grade systems for clinical applications. Responsibilities include people leadership, quarterly planning, technical architecture, design reviews, model governance, ML SDLC oversight, and deployment of reliable microservices on Kubernetes. The role partners with product, data science, and clinical stakeholders while ensuring safety, operational excellence, cloud scalability, and compliance for sensitive healthcare data.

Analyze large datasets, identify meaningful patterns, develop machine learning models, and deliver actionable insights for business decisions. Collaborate with cross-functional teams to understand data needs, communicate findings clearly to stakeholders, and stay current with advances in data science and AI technologies.

Leads enterprise AI tooling and security engineering, designing scalable cloud platforms and secure AI applications. Responsibilities include protecting models, agents, prompts, data, APIs, and outputs; securing the AI/ML lifecycle; implementing identity, encryption, monitoring, threat detection, adversarial testing, and incident response; and establishing engineering standards. The role mentors engineers, influences architecture and technology strategy, and partners with governance, risk, compliance, and business teams to support responsible AI adoption.

Leads complex enterprise SaaS delivery programs for major banks, owning governance, client and executive relationships, commercial controls, risk management, regulatory deadlines, third-party coordination, and successful go-live. The role requires deep financial crime compliance technology experience, including AML, KYC, transaction monitoring, sanctions screening, or case management platforms, plus proven Tier 1 bank implementations, program turnaround expertise, cloud delivery, and senior stakeholder credibility.

Lead independent validation and ongoing monitoring of complex financial and analytics models, including ALM, loss forecasting, loan transition, corporate finance, and engagement models. Identify weaknesses, communicate findings, guide remediation, and strengthen model governance. Collaborate with Finance, Quantitative Research, Growth Analytics, Internal Audit, Internal Controls, Accounting, and Compliance to maintain Affirm’s model risk framework and address audit, regulatory, and examiner requests.

Leads KeyBank’s Red Team and offensive security program, including adversary emulation, penetration testing, physical and application assessments, cloud security testing, AI security evaluations, and purple team exercises. Develops testing strategy, methodologies, tooling, metrics, and maturity roadmaps; mentors engineers; coordinates internal and third-party engagements; validates remediation and attack paths; and presents findings and strategic recommendations to executives and cybersecurity stakeholders.

Lead G2’s experimentation practice across products and digital marketplaces. Design experimentation standards, causal inference methods, metrics, guardrails, and analysis approaches; partner with product and engineering to implement experimentation platforms and instrumentation. Build models, design auctions, ship production systems, evaluate modern statistical methods, and address marketplace interference and low-traffic constraints. Mentor data scientists and evangelize rigorous data science practices across the organization.

Leads Kapitus’ core lending product portfolio, including term loans and lines of credit. Owns product P&L, strategy, pricing, go-to-market execution, competitive intelligence, roadmap prioritization, regulatory alignment, and financial outcomes. Partners with Product Delivery, Risk, Finance, Sales, Marketing, Operations, Compliance, and executives. Manages and develops a team of product managers while identifying opportunities for AI and machine learning to improve underwriting, decisioning, offers, and borrower communications.

Leads Tala’s Machine Learning Engineering team in building and operating platforms for model development, real-time inference, streaming features, batch processing, deployment, monitoring, and production reliability. Manages and develops 4–6 engineers, owns delivery and prioritization, provides architectural leadership, improves engineering practices and SLOs, and partners with Data Science, Data Engineering, Product, Credit, and Business Development teams.

Leads enterprise innovation strategy and cross-domain solution architecture across AI, data, cloud, software engineering, ITSM, DevSecOps, and cybersecurity. Designs scalable, secure solutions; develops reusable accelerators and innovation frameworks; supports federal proposals, capture efforts, and technical writing; advises senior government stakeholders; and drives cross-functional collaboration, capability development, and technology adoption in GovCon environments.

Sell Omnifold’s AI-driven forecasting and optimization platform to enterprise customers across supply chain, manufacturing, CPG, retail, and logistics. Responsibilities include self-sourcing pipeline, engaging senior executives, managing complex multi-stakeholder sales cycles, quantifying ROI, closing six- and seven-figure deals, maintaining CRM accuracy, forecasting, and helping build the company’s sales playbook and go-to-market strategy.

Develop and lead data science and machine learning initiatives, including exploratory analysis, predictive modeling, experimentation, recommendation systems, user classification, model monitoring, and production deployment. Partner with product, marketing, analytics, and engineering teams to convert user insights into automated services. Manage projects throughout their lifecycle, support strategic ML planning, and deliver solutions for personalization, cross-selling, and retargeting.