Top AI Jobs in San Francisco Bay Area, CA

Hands-on machine vision applications engineer responsible for lab testing, camera and optical setup, proof-of-concept builds, technical reporting, technology evaluation, customer-site troubleshooting, and deployment support. The role also includes image collection, labeling, model training, model evaluation, camera calibration, hardware evaluation, and building internal test resources. Candidates need machine vision fundamentals, AI vision familiarity, troubleshooting ability, and comfort working with hardware, industrial automation, and manufacturing customers.

Build Syntro’s technical foundation across the stack, including systems that structure procurement data from emails, spreadsheets, ERP records, quotes, and supplier information. Design reliable AI agents that reason and act under uncertainty, establish scalable architecture and engineering standards, operate production systems, and work closely with customers. The role offers significant ownership over technical decisions, product direction, infrastructure, observability, and eventually the engineering team.

Leads research engineers building AI-based monitoring and observability systems for training and deployment. Responsibilities include developing frameworks for analyzing large unstructured datasets, building agentic integrations, partnering with safety and research teams, setting technical strategy, coaching employees, recruiting, and improving team processes. The role spans infrastructure, user-facing applications, LLM development, and tools that support AI oversight, misuse detection, and alignment efforts.

Lead ZAIDYN's AI Engineering function to design, build, and ship an enterprise-grade agentic AI platform. Own architecture, integrations (AWS Bedrock/AgentCore), LLMOps/eval frameworks, observability, governance, and team hiring/operations. Ensure production readiness, cost/latency controls, auditability, and cross-functional delivery with product and QA while representing the platform externally.

The AI Engineering Specialist will oversee project tasks, manage expectations, mentor junior members, and design scalable AI systems while working with advanced AI models and ML pipelines.

Build datasets, evaluations, and scalable data infrastructure to improve frontier AI models for scientific and biological applications. Analyze model failure modes, run experiments, translate scientific expertise into rigorous evaluation criteria, and collaborate with scientists and AI labs. The role requires working at the intersection of software engineering, biology, and frontier AI in an in-person, fast-paced San Francisco environment.

Leads Fusion’s Technical Architecture practice while personally building production AI and LLM tooling for Professional Services. Responsibilities include managing and mentoring architects, setting architecture standards, supporting enterprise presales and regulated customers, modernizing delivery infrastructure, establishing AI security guardrails, evaluating emerging AI capabilities, and driving adoption through training and enablement. The role requires deep Salesforce or ServiceNow expertise, hands-on software development, enterprise integration knowledge, and executive-level customer engagement.

Leads Unanet’s internal data strategy and architecture for enterprise AI. Defines the shared data foundation, target architecture, governance standards, roadmap, and reusable approaches for AI assistants, agents, and workflows. Evaluates platforms and integration options, validates technical solutions, and coordinates IT, Security, Legal, Engineering, business owners, and system specialists. Advises senior leaders, establishes data quality and stewardship requirements, and helps determine when data is ready to support scalable AI initiatives.

Design, build, deploy, and maintain resilient, scalable backend services and platform components for Toast's Voice AI platform. Lead cross-cutting architecture and projects, integrate AI platforms (LLMs), implement observability and evaluation for AI systems, set engineering standards, and mentor engineers.

Own the reliability and quality of an AI copilot for a trading platform. Build evaluation frameworks, benchmarks, quality gates, monitoring, incident response, and model improvement workflows. Partner with engineering and product to create safe, auditable tool interactions and improve assistant behavior. Develop domain expertise in trading, risk, margin, execution, and portfolio reasoning while operating across model, backend, and frontend systems.

As an AI Engineer, you will develop and optimize AI systems for legal tasks, work on integrating models, and establish evaluation frameworks to enhance decision-making capabilities in complex legal workflows.

Build and deploy AI-enabled workflows across internal departments, partnering with business leaders and subject-matter experts. Design agentic solutions, evaluations, integrations, tools, and reusable platform capabilities. Establish operating models for discovery, onboarding, adoption, production support, and continuous improvement. Translate deployment insights into enterprise AI platform investments while advising senior technical and business stakeholders.

Develop and productionize machine learning systems for search, retrieval, ranking, recommendations, conversational experiences, and AI agents. Own projects across the ML lifecycle, build evaluation datasets and benchmarks, conduct offline and online evaluations, analyze model quality, and improve system performance. Design scalable architectures addressing reliability, latency, privacy, and cost. Collaborate across product and engineering teams, communicate technical decisions, mentor engineers, and contribute to ML best practices.

Leads Utility’s AI practice by defining its roadmap, overseeing AI research and deployment, identifying client opportunities, mentoring AI teams, and establishing responsible AI practices. The role combines technical leadership, product strategy, client advisory, and operational execution across machine learning, generative AI, and intelligent automation initiatives.

Own production operations for workplace AI platforms, including configuration, integrations, observability, secrets, access controls, model and prompt changes, benchmarking, and incident response. Translate technical findings into governance, risk, compliance, and training materials while collaborating with Security, Legal, HR, and business stakeholders. Investigate failures, implement mitigations, document root causes, and maintain reliable, secure AI services.

Lead design and delivery of advanced data and ML solutions, performing exploratory analysis, statistical modeling, and visualization to inform strategy. Manage and coach teams, collaborate with clients to validate outcomes, and improve analytics processes and data quality to drive business decisions.

Lead and oversee multiple multidisciplinary teams to architect, develop, deploy, monitor, and maintain full-stack AI solutions (including LLM integrations). Provide strategic and technical leadership, drive experimentation and CI/CD practices, ensure quality and stakeholder alignment, promote innovation, and mentor senior and junior team members to deliver business-aligned AI outcomes.

Leads teams in designing and deploying scalable AI and machine learning solutions for consulting clients. Responsibilities include data wrangling, complex analysis, data modeling, AI system implementation, data pipeline and infrastructure oversight, deep learning, neural networks, data quality validation, and stakeholder collaboration. The manager coaches team members, manages performance, supports innovation, and applies Python, Java, and cloud technologies to build production-ready AI applications.

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 and coach teams to design, develop, and deliver production-grade AI and data solutions for clients. Manage client accounts, ensure quality and timelines, analyze complex datasets, implement best practices, and drive continuous improvement while fostering client relationships and technical excellence.

Lead client engagements to assess business challenges, define enterprise data and AI strategies, develop roadmaps, guide solution design and delivery, provide technical leadership and mentoring, and support practice growth via presales and thought leadership.

Supports AI engineering initiatives at Vantor, contributing to spatial intelligence solutions and helping develop technologies that enable customers to understand current and future conditions. The posting provides limited role-specific responsibilities but emphasizes problem-solving, innovation, collaboration, and mission-focused work. Applicants must qualify as a U.S. Person under applicable export control and ITAR requirements.

Develop and operate production ML and AI systems powering patient experiences such as matching, ranking, recommendations, onboarding, and personalization. Build reusable ML infrastructure, pipelines, evaluation, observability, and model-serving capabilities. Provide technical leadership across the ML lifecycle, guide architecture, evaluate custom versus foundation-model approaches, and partner with ML and Patient Engineering teams to deliver reliable, scalable AI products.

The AI Applications Engineer will prototype AI-driven solutions, collaborate with stakeholders, and create reusable components to address business challenges.

Design and implement AI agents, plugins, automations, and enterprise integrations for HR Technology platforms. Lead requirements gathering, technical analysis, solution design, testing, documentation, deployment, security, and data integrity efforts across HR, IT, and business stakeholders. Integrate platforms including ServiceNow, Workday, and other enterprise applications while supporting the HR automation and AI roadmap.