Top AI Engineer Jobs

Develops and deploys AI/ML applications for autonomy, pattern recognition, target detection, decision support, signals processing, and robotics. Responsibilities include creating mathematical and statistical models, processing heterogeneous datasets, training and fine-tuning machine learning systems, modifying deep learning architectures, evaluating performance, and presenting technical results. The role also involves rapid prototyping, production deployment, cross-functional collaboration, and work involving LLMs, NLP, computer vision, sensor fusion, and explainable AI.

Develop and maintain the U.S. Census Bureau’s LLM Autocoder using Python, LLMs, prompt engineering, text classification, structured outputs, and testing. Build survey-specific pilots, troubleshoot production issues, evaluate model changes, and collaborate with data scientists and MLOps engineers on AWS deployment, rollback, and verification. Maintain documentation and support government handoff while meeting Census security and operational requirements.

Build and maintain responsive WordPress websites, landing pages, reusable templates, and digital lead-generation experiences. Use AI-assisted development tools to accelerate coding, publishing, testing, and troubleshooting while reviewing code for quality and security. Implement technical SEO, analytics, conversion tracking, integrations, performance improvements, and QA. Manage themes, plugins, staging, deployment, backups, and website security while supporting scalable publishing workflows and collaborating with marketing and business teams.

Leads enterprise platform engineering and AI enablement by building secure, scalable AWS platforms, internal developer services, automation, CI/CD standards, infrastructure-as-code practices, monitoring, reliability controls, and governance. Partners with architecture, security, infrastructure, data, and delivery teams to operationalize AI, machine learning, analytics, and generative AI workloads. Advises senior leadership, drives technical initiatives, improves developer productivity, mentors engineers, and supports regulated-industry compliance.

The Senior AI/ML Capacity Engineer will develop capacity planning models, design analytical tools, and collaborate with teams to optimize costs and efficiencies.

Build scalable data pipelines, automation workflows, internal tools, and AI-powered quality-control systems. Lead data collection projects for frontier AI labs, establish quality frameworks, improve customer support processes, and manage cross-functional execution. Collaborate with technical and non-technical stakeholders to solve ambiguous operational challenges and deliver datasets and systems that improve advanced AI models.

Lead architecture and implementation of AI-security products, define technical direction, drive cross-team initiatives, design secure scalable backend systems, and address systemic risks while remaining hands-on in coding, prototyping, and debugging.

Design, develop, and maintain scalable backend systems for automated order-taking platforms, collaborating with teams to integrate AI models and optimize performance across noisy environments.

As a Software Engineer at Deepgram for Restaurants, you'll design and maintain scalable backend systems for automated ordering, integrating AI models, optimizing performance, and ensuring smooth interactions with restaurant software.

Work on AI-powered Notion features: prototype and ship model-powered product improvements, integrate and productionize models, improve model performance and reliability, and build evaluation frameworks and experiments to measure and improve quality.

As a Senior AI/ML Engineer, you will manage the AI/ML lifecycle, develop predictive models, conduct anomaly detection, and integrate AI capabilities into the Confido platform.

Lead design and delivery of a web channel framework using React/TypeScript. Drive engineering standards, testing (unit to end-to-end), CI/CD, performance optimization, RESTful services, and cross-functional agile collaboration to build a scalable SPA platform.

AI/ML Engineers will build and deploy AI-native products, autonomous agents, LLM applications, RAG systems, and production ML pipelines. Responsibilities may include integrating AI into crypto infrastructure and consumer products, fine-tuning and evaluating models, optimizing inference, and developing agentic workflows and machine-to-machine payment systems. Engineers will work end-to-end with high-ownership teams in fast-moving environments.

Build customer-facing AI features and horizontal infrastructure to deliver trustworthy, auditable AI automation for financial accounting. Own full-stack feature development, measure and improve AI product efficacy, and make strategic product and technical decisions.

Lead the architecture and development of scalable platform capabilities spanning user interfaces, backend services, APIs, cloud infrastructure, and AI or agentic systems. Drive technical strategy, full-cycle implementations, and architectural improvements while ensuring security, reliability, performance, observability, and auditability. Collaborate with product, design, security, reliability, and platform engineering teams to simplify infrastructure operations and improve developer workflows.

Leads design, deployment, operation, security, and optimization of Starshield’s Top Secret data center networks supporting large-scale AI clusters. Responsibilities include optical and copper connectivity, routing and switching, automation, capacity planning, troubleshooting, reliability improvements, network integration, firmware updates, and mentoring engineers. The role requires collaboration with ML, hardware, software, and network teams, on-call availability, extended hours, and domestic or international travel as needed.

Lead the design, deployment, operation, and optimization of secure, high-performance data center networks supporting large-scale AI clusters and national security missions. Responsibilities include optical and copper connectivity, network automation, capacity planning, troubleshooting, security improvements, hardware and firmware integration, performance monitoring, and mentoring junior engineers. The role requires collaboration with ML, hardware, software, and network teams, on-call availability, extended hours when needed, travel, and obtaining a Top Secret clearance.

Design, deploy, operate, and optimize secure, high-speed data center networks supporting Top Secret AI infrastructure and national security missions. Responsibilities include optical and copper connectivity for large GPU clusters, network automation, capacity planning, performance monitoring, troubleshooting, security improvements, configuration and firmware updates, and cross-functional network integration. The role also mentors junior engineers, leads technical initiatives, participates in on-call rotations, and may require extended hours and domestic or global travel.

Design, deploy, operate, and scale GPU/CPU infrastructure supporting classified AI and national security missions. Responsibilities include managing Kubernetes and AI clusters, automating on-premise infrastructure deployments, supporting GPU-as-a-service platforms, operating databases, monitoring, and distributed storage, and improving service reliability, scalability, and availability. The role collaborates closely with AI engineers and requires Linux, infrastructure automation, containerization, scripting, software development, and security-clearance eligibility.

Design, deploy, operate, and scale GPU/CPU infrastructure supporting classified national security missions. Responsibilities include managing Top Secret datacenter deployments, GPU-as-a-service platforms, large-scale AI clusters, Kubernetes, operating systems, databases, monitoring, distributed storage, automation, and high-availability services. The role partners with AI engineers, improves service lifecycles, and develops solutions for performance, reliability, and operational scalability.

Design, deploy, operate, and scale GPU and CPU infrastructure supporting classified national security missions. Manage Kubernetes and AI clusters, Linux systems, databases, monitoring, distributed storage, virtualization, and GPU-as-a-service platforms. Build automation for large-scale on-premise environments, improve reliability and performance, collaborate with AI engineers and customers, and mentor junior engineers. Lead technical decisions and service lifecycles while supporting high availability across Top Secret data centers.

Design, deploy, operate, and scale GPU/CPU infrastructure supporting classified national security missions. Manage Kubernetes and AI clusters, bare-metal and virtualized platforms, operating systems, databases, monitoring, and distributed storage. Build automation with infrastructure tools, improve service availability and performance, collaborate with AI engineers, mentor junior staff, and provide technical leadership. The role requires obtaining and maintaining a Top Secret clearance, extended-hours availability, and future domestic and international travel.

Design, deploy, operate, and scale GPU/CPU infrastructure for classified data centers and AI clusters. Build automation for on-premise Kubernetes clusters and operating systems, manage databases, monitoring, distributed storage, and GPU-as-a-service platforms, and improve service reliability. Collaborate with AI engineers, lead lifecycle operations, mentor junior engineers, and guide technical excellence across the team.

Designs, deploys, operates, and improves high-speed data center networks supporting AI clusters and national security missions. Responsibilities include optical and copper connectivity, network security, performance monitoring, capacity planning, troubleshooting, automation, hardware deployment, configuration, firmware updates, and network integration. The role collaborates with ML, hardware, software, and network engineering teams, supports Top Secret data centers, participates in on-call rotations, and requires obtaining and maintaining a Top Secret clearance.

Deploys, operates, and improves secure network infrastructure for Top Secret AI data centers supporting Starshield missions. Designs high-speed copper and optical connectivity for large GPU clusters, translates ML workload needs into network topologies, automates device provisioning, monitors performance, plans capacity, troubleshoots failures, and leads network integration. The role also involves hardware deployment, security improvements, configuration and firmware updates, on-call rotations, extended hours, and future domestic and international travel.