Top AI & Machine Learning Jobs

Serve as the technical face to customers, running evaluations, scripting, benchmarking, and validating physics-based ML models. Scope and translate customer requirements into engineering work, lead technical proposals and demos, diagnose model failures, and establish the template for the U.S. technical team while supporting secure, restricted-access program reviews.

Early-career software engineer who writes Python to integrate LLMs and AI services into AWS-hosted applications. Build APIs, data pipelines, embeddings/vector search, and support deployment, testing, and monitoring of AI features while following responsible AI and software engineering best practices.

Build and productionize end-to-end AI-powered product features: prototype and iterate on prompts, retrieval flows, evals, backend systems, APIs, data models, and UX to deliver reliable, customer-facing LLM workflows.

Design, build, and maintain AI-enhanced VFX pipeline integrations and artist tools. Automate workflows, manage model training/fine-tuning, integrate DCC apps, optimize performance, and collaborate across creative and engineering teams to deliver scalable, production-ready AI solutions.

Train and iterate custom ML models on manufacturing and design data to estimate cost and complexity, generate designs, and extract structured data from engineering documents. Build end-to-end pipelines from data cleaning and labeling through training, evaluation, and deployment. Collaborate with engineering and manufacturing teams to source datasets and identify opportunities to improve workflows with custom models.

Lead customer-facing deployments and integrations of the AI platform across Bay Area sites. Port cloud features to on-prem and air-gapped environments, manage and debug cloud deployments (AWS, Azure, GCP, OpenShift), and collaborate with customers to develop workflow-specific features while learning hardware design concepts as needed.

Two-year rotational program for recent graduates to identify, design, build, and deploy AI-powered automations across manufacturing and business functions. Program members complete six four-month rotations, deliver production-ready solutions, validate data integrity, maintain documentation, present results to leadership, and train incoming members.

Design, train, and deploy machine learning models for detecting malicious content, working with large datasets and collaborating with teams to enhance system scalability.

Design and operate scalable infrastructure and automation for real-time video ML workloads. Build Kubernetes orchestration, CI/CD pipelines, IaC, monitoring, and high-performance Linux/networking systems for cloud and edge deployments, collaborating with ML engineers to validate and scale model deployments.

The Machine Learning Researcher will build predictive models using deep learning, explore strategies to enhance portfolio performance, and update models based on research. They should have a strong foundation in ML with hands-on experience in relevant domains.