Top AI Jobs in Austin, TX

Design and build a global, serverless AI inference platform running on heterogeneous GPUs and accelerators. Optimize model scheduling, request routing, caching, and load balancing for low latency. Improve reliability and observability, lead cross-functional projects, and mentor junior engineers.

This role involves developing and maintaining CI/CD pipelines, enhancing deployment processes, ensuring infrastructure reliability, and promoting best practices within the AIDR platform team.

Lead architecture and development of Back-End CAD flow (FlowJam), partner with Physical Design teams to define synthesis/place-and-route/timing and power methodologies for advanced nodes, improve QoR and automation, integrate AI-driven optimization, collaborate with EDA vendors, and mentor engineers.

Define and implement the physical design flow; drive IP and SoC physical design execution; collaborate with CAD and cross-disciplinary teams; mentor and hire engineers; work hands-on with advanced process nodes to achieve PPA, power, and timing signoff.

The Principal AI Compiler Engineer designs hardware for AI, ensuring models translate effectively to silicon and perform optimally in 5G applications.

The Principal AI Model Architect's role includes optimizing model architectures for new hardware, translating AI algorithms into hardware specifications, and projecting performance for silicon design.

Lead and define AI architecture, ensuring scalable, reliable AI systems while mentoring engineers and collaborating with product teams.

Lead end-to-end delivery of AI and ML services within Managed Services. Manage project planning, budgeting, execution, and quality. Mentor and develop team members, cultivate client relationships, implement model monitoring and operationalization practices, and collaborate with architects and engineers to ensure compliant, reusable AI solutions.

The Senior Backend Engineer will design, build, and scale AI-driven operations, manage the product lifecycle, and implement AI technologies while ensuring data security and system performance.

Lead strategy and roadmap for CrowdStrike's Charlotte GenAI platform, deliver developer-first AI capabilities, partner with engineering and data science, drive cross-functional delivery and adoption, evangelize GenAI across the Falcon ecosystem, and ensure platform scalability, performance, and security.

As a Senior AI/ML Engineer, you'll enhance developer productivity by leading CI solutions, mentoring engineers, and implementing scalable systems.

The role involves architecting AI applications, delivering scalable solutions, conducting research, and implementing high-quality code for cloud platforms. Requires collaboration and effective communication.

Manage the full eDiscovery lifecycle for litigation matters: scope and execute ESI collection, processing, review, and production. Use Relativity One, BrainSpace, iPro and other tools, ensure QC and metrics reporting, coordinate cross-functional stakeholders, mentor teams, and produce attorney-facing reports.

Design, build, and maintain globally distributed, fault-tolerant backend microservices and data pipelines. Integrate and refine Large Language Models, collaborate cross-functionally, ensure high-quality code, testing, monitoring, and mentor other engineers while owning features end-to-end.

Lead design and delivery of the AI-powered creative operating system connecting audience intelligence, briefs, concepting, asset production, and performance feedback. Build and standardize video and image AI pipelines, Figma automation, tool stack selection, and workflows that scale creative output. Embed with creative teams to ship production-ready systems, evaluate emerging capabilities, and ensure measurable increases in output with flat headcount.

Design and implement scalable ML infrastructure solutions, mentor junior engineers, own technical projects, and collaborate across teams to solve complex AI/ML problems.

The Principal AI/ML Engineer will lead the AV ML Infra team at GM, focusing on developing scalable ML infrastructure and guiding cross-functional collaboration while driving technical projects from inception to completion.

The Staff AI/ML Engineer will design and implement scalable ML infrastructure solutions, lead projects, mentor peers, and enhance ML productivity at GM.

Lead and scale DBS-driven innovation by coaching leaders, executing OpCo collaboration, guiding strategic initiatives aligned to Innovation KPIs (IPV, RA), mentoring teams, and driving adoption of DBS tools and best practices. Advocate for tool improvements and deliver new product developments using DBS fundamentals.

Lead and scale engineering teams to build AI-native platforms across IT, OT, networking, and cybersecurity. Drive delivery of distributed, scalable backend systems, establish engineering processes, embed LLM/ML into production, champion AI-assisted development practices, partner with executives on strategy, and mentor senior technical leaders. Hybrid role in Austin with two onsite days weekly.

Design and build AI-native, high-performance distributed backend platforms for IT/OT/cybersecurity. Integrate LLMs and ML into production workflows, develop data pipelines and real-time processing, mentor engineers, and drive architectural direction and AI-assisted engineering practices.

Execute verification tests for flight software across spacecraft and launch vehicle programs. Develop and run automated test scripts in SIL/PIL/HIL environments, document results, track defects, support root cause analysis, assist hardware integration and simulator setup, and collaborate with engineering teams to ensure software quality under senior guidance.

Lead and manage a Medical Science Liaison (MSL) team to execute medical plans, engage KOLs and healthcare stakeholders, disseminate scientific data, collaborate cross-functionally for product initiatives, ensure regulatory compliance, monitor scientific trends, and represent the company at scientific events. Requires deep oncology and molecular biology expertise.

Embed with non-revenue teams to discover high-leverage workflows, build and ship AI agents/automations on shared infrastructure, coach teams to self-sufficiency, productize durable solutions, and scale reproducible playbooks across the company.

Build and operate AI-driven People Ops systems on the Cloudflare developer platform: ship production workflows for hiring, onboarding, recruiting automation, self-service, AI copilots, data reconciliation, observable audit pipelines, and custom interview tooling. Integrate systems securely, implement authorization/audit logging, and work cross-functionally with HR, Legal, IT, and Security.