Artificial Intelligence Jobs in Oakland, CA

As an AI Platform Engineer, you will design and develop AI-driven backend solutions, optimize performance, and collaborate with customers and teams.

Work as an AI intern building end-to-end AI/ML solutions for R&D and manufacturing. Tasks include data exploration, pipeline engineering, model development, API and AWS integrations, LLM-powered features, and shipping dashboards and agentic workflows while collaborating with biologists and engineers.

The role involves designing and developing high-performance web apps, improving user interfaces, maintaining component libraries, and ensuring code quality through comprehensive testing and collaboration with other teams.

Develop, train, validate, and document ML and LLM-based models on clinical datasets, ensure GxP-compliant data pipelines and QA, build Databricks/AWS-based pipelines, create dashboards, collaborate with cross-functional clinical teams, and contribute to scientific publications.

Design, build, and operate AWS-native AI/ML systems: RAG pipelines, fine-tuned LLMs, and microservices. Implement IaC (Terraform), CI/CD, policy guardrails, and production deployments integrating Bedrock/SageMaker, LangChain, and telemetry for secure, scalable enterprise use.

Build and operate secure, scalable ML pipelines and hybrid GPU infrastructure for training, fine-tuning, serving, and governing open-source LLMs and agentic apps. Implement CI/CD, model versioning, observability, benchmarking, security controls, and integration with RAG/agent tools and vector DBs to support production deployments across tenants.

Design, train, evaluate, and optimize agent-native LLMs and RAG pipelines for enterprise use. Build training and RL pipelines (RLHF/DPO/PPO), embedding-based memory, evaluation harnesses, observability, and inference optimization across cloud and on-prem environments.

Design, build, and deploy reliable, outcome-driven AI systems and agentic workflows that plan, reason, and act across enterprise systems. Integrate LLMs into production, work with structured and unstructured data to ground models in business context, and partner with product to ship end-to-end capabilities.

Design behavioral specs, harnesses, and validation systems so AI agents implement reliable full-stack features. Build CI gates, structural tests, linting, knowledge bases, and end-to-end verification. Diagnose failures across spec, harness, and agent layers. Architect and operate production systems across cloud and on-prem environments for regulated energy deployments, prioritizing reliability, observability, and graceful degradation.

S32 seeks Applied AI Research Scientists to explore new approaches, algorithms, and methodologies to advance AI systems across portfolio companies. Candidates will drive research, shape company direction, and collaborate with founders to apply research outcomes to product and business needs.

Seeking Applied AI Research Scientists to develop and explore new AI approaches, algorithms, and methodologies to drive AI systems across S32 portfolio companies and shape company direction.

The AI Engineer will develop scalable AI systems, optimize LLMs, maintain data workflows, and ensure system resilience while collaborating on innovative solutions.

As an AI/ML Platform Engineer, you will develop APIs, data pipelines, and workflows to support AI capabilities for scientific research, ensuring system reliability and scalability.

Develop CAD automation pipelines and collaborate with teams to optimize designs for micromachines, ensuring manufacturability and functionality.

Build and scale AI data and ML infrastructure: evaluation systems, fine-tuning pipelines, agent-first product surfaces, high-throughput data workflows, and integrations of new models into production.

Senior technical leader responsible for architecting production-grade AI infrastructure for media & entertainment partners. Translate business needs into scalable GPU, storage, networking and inference solutions; validate ISV integrations; influence product roadmap; engage CTO-level stakeholders; and grow a team as the vertical scales.

The Staff Backend Engineer is responsible for designing and developing AI platforms, backend services, and APIs, ensuring scalability and reliability while collaborating with cross-functional teams and mentoring engineers.

As a Founding Account Executive, you will drive the sales cycle, generate leads, become a product expert, and expand customer accounts, all while serving as a trusted advisor on voice AI solutions.

The Senior Applied AI Engineer will build AI-driven interactive product demos, collaborating with design and engineering teams to create intelligent multimodal experiences.

As a Staff/Principal AI Engineer, you'll design and implement AI strategies for legal tech, lead engineering teams, and guide AI projects while collaborating across departments.

Lead AI product strategy and execution for an intelligent manufacturing platform: define AI vision, own model lifecycle and infrastructure, embed AI into quoting and fulfillment applications, run experiments and metrics, and align cross-functional teams to commercialize AI capabilities.

Lead strategy and development of AI and technology products, managing cross-functional teams to enhance legal workflows and compliance standards.

The Sales Strategy and Operations Manager leads complex sales opportunities, develops ROI models, engages executives, and coordinates cross-functional input for compelling proposals.

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

Lead AI initiatives, establish strategy, and develop generative AI applications. Collaborate with teams to build and optimize financial products.