Machine Learning Jobs in Oakland, CA

As a Staff Machine Learning Engineer, you will enhance credit modeling, manage full credit modeling stacks, and support innovations within regulated banking frameworks.

Lead AI engineering teams to design, build, and deploy end-to-end AI solutions. Manage client relationships, plan and deliver projects, mentor staff, drive adoption of cloud-native microservices, CI/CD, vector databases and orchestration tools, and ensure high standards of quality, innovation, and compliance.

Lead teams applying advanced data science and machine learning to large-scale claims, clinical, and member data to generate actionable insights that reduce cost of care and improve population health. Manage client relationships, mentor staff, ensure project delivery and quality, develop payer-focused analytics products, present findings to senior stakeholders, and promote continuous improvement and knowledge sharing.

Design and implement AI systems and scalable machine learning models, perform data wrangling and software engineering to deploy AI solutions, interpret data for client recommendations, collaborate across teams, uphold technical standards, and build client relationships while navigating complex, ambiguous problems.

Leverage advanced analytics, data manipulation, visualization, statistical modeling, predictive analytics, and machine learning to generate client insights and recommendations. Apply Adobe Experience Cloud solutions to support business transformation and strategic decision-making. Build client relationships, manage and inspire teams, navigate complex engagements, uphold professional standards, and deliver quality outcomes while developing technical and consulting expertise.

Leads data analysis and advanced analytics workstreams for clients, using statistical modeling, machine learning, data visualization, and Adobe Experience Cloud technologies to improve operations and strategic decision-making. Manages project planning, budgeting, execution, and completion while mentoring teams, maintaining data integrity and security, building Tableau and Power BI dashboards, identifying business opportunities, and integrating innovative analytics practices.

Lead and manage internal audit and SOX engagements, implement audit methodologies, use AI and risk technology to optimize processes, assess controls and financial statements, mentor staff, produce audit reports, and collaborate with stakeholders to mitigate risks and support client growth.

Senior-level engineer delivering analytics and ML-Ops solutions for healthcare payers. Design and implement analytics platforms on Databricks, develop CI/CD and provisioning patterns, collaborate with data scientists, mentor juniors, and build client relationships to drive actionable insights and operational improvements.

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.

Build and deploy agentic and generative AI systems that automate risk and compliance investigations. Own full-stack ML systems, including data integrations, prompt tuning, orchestration, evaluation, productionization, monitoring, and transformer-based modeling across transaction, graph, text, and profile data. Collaborate with product, engineering, platform, and operations teams while leading strategic roadmaps and delivering scalable production systems.

Build and deploy agentic and generative AI copilot and autopilot systems for risk and compliance automation. Own end-to-end ML systems, including data integrations, prompt tuning, orchestration, evaluation, productionization, monitoring, and transformer-based model development. Collaborate with product, engineering, platform, and operations teams to improve fraud detection and analyst productivity. Drive strategic roadmaps and cross-functional programs with significant business impact.

Build and maintain scalable, reliable ML data platform systems to support dataset generation, model training, analytics, monitoring, and large-scale inference. Collaborate with ML, software, and infrastructure engineers to design cost-efficient data lake and training infrastructure using vendor and open-source tools to enable next-generation ML models.

Design, build, and operate production ML decision systems to detect and prevent payment fraud, account takeover, scams, and other abuse. Integrate diverse signals into low-latency serving and batch scoring, own feature pipelines and model lifecycle, develop AI-assisted triage and feedback loops, and partner cross-functionally to balance fraud reduction with legitimate customer access.

Design, build, and operate production ML systems that generate trusted signals for ranking, retrieval, recommendations, propensity/churn/LTV, and next-best-action decisioning. Define signal/data contracts, own feature and candidate generation through serving, experimentation, monitoring, and feedback loops, and evaluate long-term business impact, trust, fairness, and compliance. Partner across product, data, modeling, risk, and compliance and apply AI/agents to accelerate engineering and operations.

Own the end-to-end creation and optimization of performance-driven advertising across TikTok, Meta, YouTube, CTV, and emerging channels. Develop concepts, scripts, hooks, creative frameworks, briefs, and edited video assets while maintaining strong visual and brand quality. Use performance data, platform trends, AI tools, and media insights to improve creative effectiveness. Direct agency and production partners, collaborate with growth and analytics teams, and scale Jerry’s creative output.

Lead data-driven business operations initiatives spanning customer acquisition, carrier and partnership growth, product development, and operational efficiency. Design, execute, and analyze A/B experiments; apply machine learning and complex data analysis to identify scalable growth opportunities; communicate insights to marketing, product, business development, frontline teams, and executives; and automate manual processes.

Drive data-informed decisions across growth, product, and business initiatives. Partner with marketing, product, and business development teams; analyze customer performance; design and evaluate A/B experiments; identify acquisition and partnership growth levers; and automate manual processes to improve operational efficiency. The role requires rigorous problem solving, advanced data analysis, SQL proficiency, and communication with both frontline teams and executives.

Drive data-informed decisions across carrier growth, product launches, user acquisition, and partnership initiatives. Partner with marketing, product, and business development teams; design and analyze A/B experiments; identify scalable growth levers; conduct complex analyses using machine learning models; and automate manual processes to improve operational efficiency. The role requires strong problem-solving, quantitative analysis, SQL, and communication skills.

Lead data-driven business operations initiatives across acquisition, partnerships, and new product development. Partner with marketing, product, and business development teams to analyze customer performance, design and evaluate A/B experiments, identify growth levers, and improve operational efficiency through automation. Use SQL and advanced machine learning models to generate insights that inform profitable, scalable business strategies and communicate recommendations to audiences from frontline staff to executives.

As an Applied AI Engineer at Luminai, you will design experiments, optimize machine learning models, and enhance AI platforms for healthcare automation.

The Head of Clinical Development & Strategy will lead clinical strategy, develop product profiles for early-stage assets, and shape collaborations with pharma partners, focusing on medical necessity and strategic direction.

The Machine Learning Scientist will develop reinforcement learning algorithms for protein design, collaborate with teams, and shape machine learning strategies.

Lead a major product area end-to-end: set strategy and KPIs, define customer personas and market thesis, prioritize features, drive execution with engineering, and align cross-functional stakeholders to deliver high-impact AI-enabled hiring and people-analytics solutions.

Lead end-to-end performance creative: ideate, script, produce, and edit ads for paid social, CTV, and emerging channels. Translate performance data into creative direction, manage agency and production partners, and leverage AI tools to accelerate production while raising visual quality and brand standards.