Top Senior Machine Learning Jobs in Sacramento, CA

Leads the development and deployment of data solutions using Palantir Foundry and AIP. Manages engineering teams, coaches team members, oversees project planning and execution, analyzes system interactions, manages client relationships, and drives innovation. The role applies software engineering, data engineering, analytics, and AI/ML techniques to deliver scalable client solutions while maintaining technical and professional standards.

Leads the development and deployment of software and data solutions using Palantir Foundry and AI/ML technologies. Responsibilities include data engineering, analytics, system improvement, client account management, project ownership, team leadership, coaching, stakeholder engagement, and continuous improvement. The role requires building scalable applications with large datasets and delivering customer-focused solutions.

Deploys, configures, optimizes, and supports CrowdStrike Falcon’s AI-powered detection and response capabilities. The role tunes machine learning models, develops security automation playbooks, troubleshoots customer environments, integrates Falcon with existing tools, supports threat hunting and forensic analysis, and develops AI training and customer-facing materials. Requires extensive IT deployment, endpoint, security automation, operating system, AI/ML, scripting, and customer consulting experience, with travel up to 25%.

Own Secret Detection and Vulnerability Research as a product: define strategy across prevention, detection, validation, revocation, and reporting; ship detection content and intelligence with measurable quality; drive adoption, retention, and revenue; partner with engineering, research, and Field; use AI to accelerate research and productization.

Analyzes the Security for AI competitive landscape, including AI detection and response, generative AI security, autonomous agents, prompt injection, and data leakage. Partners with Product, Sales, Marketing, Strategy, and senior leaders to guide product roadmaps, go-to-market strategy, deal support, sales tactics, and competitive positioning. Conducts win/loss analysis and translates complex AI and cybersecurity concepts into executive and field-actionable guidance.

Leads financial statement audits for digital assets and financial services clients, evaluating regulatory compliance, governance, risk management, and internal controls. Applies advanced auditing and technical accounting expertise to identify material misstatements and issue audit reports. Directs complex engagements, coaches diverse teams, manages client relationships, communicates findings, and reinforces professional, independence, and ethical standards. The role also involves data analysis and exploring AI and machine learning platforms to improve processes.

Provides technical account management for enterprise customers using Samsara’s IoT platform. Builds customer relationships, troubleshoots APIs, hardware, software, and AI technologies, manages significant incidents, aligns solutions with business needs, maintains account records, and serves as a trusted technical advisor. Collaborates with internal teams, supports customer growth, contributes to TAM team development, and provides occasional travel and after-hours coverage.

Leads compliance technology oversight for transaction monitoring, sanctions screening, customer risk scoring, and AI-driven case resolution models. Builds AI-powered automation, governance frameworks, human-in-the-loop controls, real-time monitoring dashboards, data-quality controls, and model performance processes. Partners with engineering, machine learning, policy, regulators, and independent monitors to ensure models and data pipelines are explainable, auditable, exam-ready, and aligned with AML requirements across fiat and virtual currency products.

Define and own the technical vision, product strategy, roadmap, data strategy, and AI integration for CrowdStrike’s Next-Gen SIEM and log management products. Translate customer, market, and threat intelligence into shipped capabilities; lead cross-platform integration across endpoint, cloud, identity, and exposure products; and articulate the platform consolidation narrative. Engage executives, customers, analysts, sales, engineering, and product teams while driving detection, investigation, response automation, and cybersecurity thought leadership.

Build and maintain core infrastructure for developing, training, evaluating, deploying, and operating machine learning models and pipelines for Atlassian’s GenAI products. Solve complex software infrastructure and architecture challenges, lead engineers through technical projects from design to launch, and collaborate with internal teams and customers. The role involves large-scale distributed systems, data processing, cloud platforms, CI/CD, and machine learning lifecycle support.

Designs scalable data architectures, ELT/ETL pipelines, data models, quality frameworks, and self-service data platforms. Partners with engineering, product, program, leadership, and data science teams to translate business needs into technical solutions. The role includes end-to-end technical ownership, large-scale batch and streaming data processing, mentoring junior engineers, system optimization, and on-call support for platform stability.

Leads technical pre-sales for supply chain integration solutions, partnering with Sales to conduct discovery, design ERP/WMS/TMS and trading-partner architectures, run POCs, deliver demonstrations, and respond to RFPs. Advises technical and executive stakeholders on business outcomes and AI opportunities, translates capabilities into measurable ROI, and collaborates with Product, Customer Success, and Professional Services on roadmap feedback and post-sale handoffs.

Lead product strategy, roadmap, and delivery for Falcon Complete’s internal MDR tooling, including AI-powered investigation and triage, ticketing, case management, and analyst workbench systems. Partner with security operations, analysts, engineering, and data science teams to translate workflows into product requirements, prioritize automation, improve analyst productivity and response times, define success metrics, and enhance customer outcomes.

Leads client-facing generative AI and data modernization engagements, directing solution design, delivery planning, architecture, and technical decisions. Guides teams in prompt engineering, context engineering, agent orchestration, LLM evaluation, RAG, vector databases, and AI guardrails. Oversees cloud AI implementations using Gemini, Vertex AI, AWS Bedrock, or Azure AI Services; develops Python prototypes; evaluates model performance; manages workstreams and deliverables; and mentors staff on AI methods, agile delivery, and technical problem-solving.

Leads engineering teams delivering scalable AI and machine learning solutions on Google Cloud. Oversees generative AI architecture, Vertex AI, LangChain, LangGraph, LLM APIs, RAG, experimentation, evaluation, guardrails, and LLMOps. Guides technical strategy, client alignment, delivery execution, and team development while applying Python, data science, and machine learning methods to build reliable AI products.

Leads Google Cloud AI and machine learning engineering teams and client workstreams. Oversees generative AI, LLM application, agent orchestration, retrieval-augmented generation, model evaluation, prompt engineering, guardrails, and LLMOps initiatives. Reviews architecture, code quality, testing, and solution delivery using Vertex AI, LangChain, LangGraph, Python, and LLM APIs. Coaches team members, improves reusable delivery assets, and manages client relationships, timelines, quality, and expectations.

Leads client-focused generative AI and data modernization architecture, translating business needs into scalable solutions using Google Cloud, Vertex AI, LLMs, vector databases, and modern data platforms. Advises stakeholders, develops AI evaluation and guardrail practices, guides experimentation and deployment, presents technical recommendations, supports proposals, and coaches teams through complex transformation programs.

Leads the design, development, migration, and deployment of scalable data pipelines and cloud data solutions. Establishes reusable ingestion, transformation, quality, governance, compliance, and orchestration processes. Partners with business and BI stakeholders to define data requirements, support financial and operational reporting, and enable AI use cases. Requires expertise in cloud and big data technologies, DevOps, CI/CD, data management, and governance, with preferred experience in Databricks, Snowflake, data warehousing, and finance-domain data.

Build scalable systems and machine learning models that transform satellite imagery into labeled geospatial data and production computer vision products. Responsibilities include developing data and annotation pipelines, tracking lineage and versioning, deploying inference services, evaluating models, supporting cloud infrastructure, and improving labeling workflows. The role requires strong Python, cloud, containerization, CI/CD, infrastructure-as-code, production support, and deep learning expertise, with preferred experience in GCP, Vertex AI, spatial databases, and satellite imagery.

Leads end-to-end solution architecture for complex healthcare payer initiatives spanning claims, billing, enrollment, provider management, cloud modernization, and AI capabilities. Defines reusable architecture patterns, governs design decisions, translates designs into implementation artifacts, and mentors architects and engineering teams. The role partners with product, development, IT, and leadership teams to deliver cloud-native, event-driven, API-first, and AI-enabled solutions across enterprise platforms.

Drive product and business impact through statistical modeling, experiment design, Bayesian marketing analysis, machine learning, NLP, LLM applications, and classifier implementation. Build growth metrics, monitoring pipelines, evaluation datasets, and AI trigger systems across search and Duck.ai. Analyze privacy-constrained data, deploy production-grade models, optimize SQL queries, and lead complex projects from scoping through production with minimal direction.

Own the strategy, roadmap, requirements, launch, adoption, and success metrics for a technical platform. Partner with engineering, data, product, and business teams; evaluate architecture, APIs, and system tradeoffs; prioritize foundational investments against customer and revenue outcomes; and apply AI to improve platform capabilities. The role requires strong product management experience, technical depth, analytical skills, and production experience with LLM-based or ML-adjacent products.

Provides senior-level presales technical consulting for complex networking and security solutions. Partners with sales teams and customers to design WAN, data center, cloud, and security architectures; develops proposals, bills of materials, and implementation specifications; delivers technical presentations, demonstrations, proofs of concept, and training; and influences executive technology decisions. Requires extensive Juniper and networking expertise, customer-facing sales experience, and the ability to travel as business demands require.

Lead technical pre-sales for AI security solutions across SLED accounts. Responsibilities include technical discovery, architecture reviews, proof-of-concepts, product demonstrations, customer and partner training, deployment support, demo environment management, and post-sales handoffs. The role enables sales engineers and channel partners, engages technical decision-makers, and promotes secure deployment of agentic AI, including AI security best practices and integrations.

Lead go-to-market strategy and quota-carrying sales for Fortinet’s AI security solutions across SLED accounts. Build pipeline, close complex enterprise deals, conduct executive presentations and product demonstrations, train account teams and partners, and advise customers on AI governance, guardrails, runtime protection, automated red-teaming, and shadow AI. Develop strategic customer relationships, engage C-level stakeholders, and collaborate with sales, marketing, and product teams to drive adoption and revenue.