Top Artificial Intelligence Jobs

The AI Hardware Architect will analyze and design next-generation AI hardware, focusing on microarchitecture, connectivity, and system performance for GPUs and CPUs.

Lead robotics training data strategy: define formats and quality standards, oversee data collection/annotation, partner with researchers and external providers, build data acquisition plans, and deliver large-scale datasets and tooling to support robotics foundation models.

Lead deployment of NVIDIA GPU and networking solutions in customer data centers: design networks and compute/storage, debug cluster performance, run POCs, advise product roadmap, and support bring-up and customer engagements.

Lead and grow an engineering team building Agentic AI platforms and distributed edge-to-cloud systems. Drive architecture, AI model operationalization, orchestration, scalability, reliability, MLOps, and cross-functional delivery while hiring, mentoring, and setting technical strategy.

Own end-to-end delivery of a GenAI-powered security deterrence product: design services and APIs, integrate detection models with prompting and voice/TTS, build evaluation and regression suites, ensure precision and safety for real-world actuations, and drive build-vs-buy decisions while collaborating across platform, data, and ML teams.

Build and harden the cloud backbone for an agentic AI platform: scale and ensure reliability of the event pipeline, dispatch to agent/CV workflows, maintain projections and context stores, and own observability, SLOs, and operational readiness at fleet scale.

Architect and lead AI-hardware co-design solutions from research to validated proofs-of-concept. Quantify compute trade-offs with high-fidelity simulation, optimize algorithms for hardware (memory, dataflow, precision), select compute substrates from MCUs to custom accelerators, mentor engineers, and translate innovation into deployable systems while driving thought leadership in Edge AI.

Design, build, and maintain MLOps software systems and ML pipelines; deploy, test, and monitor AI/ML models on cloud-native platforms; implement ETL and data workflows; ensure model performance, security, and scalability; lead technical roadmap, mentor engineers, and evaluate emerging MLOps tools.

Own and scale the Nx-based monorepo, build system, and CI/CD to make builds, tests, and developer workflows fast, reliable, and observable. Build developer tooling, local dev stacks, and production-grade developer infra with SLOs, on-call, and measurable DX improvements.

Lead end-to-end delivery of AI deployments for financial services clients: define features, translate business needs into technical specs, run agile sprints, drive adoption and change management, ensure measurable program outcomes, and expand commercial relationships while collaborating with engineers, product, design, and investment teams.

As a research scientist, you'll design self-supervised training objectives, stress-test approaches, build evaluation protocols, and write research memos to enhance understanding of EEG signals.

Design, develop, test and deploy enterprise Java applications and AI-enabled solutions. Integrate ML/LLM models, provide Level-3 support, ensure performance, security and resiliency, and collaborate across teams to deliver production-ready payment and FX-related systems.

The Applied AI Engineer collaborates with clients to define AI strategies, identifies high-impact use cases, and builds production-ready AI systems, focusing on customer needs and delivering tangible business value.

Lead product marketing and content for a multi-product B2B SaaS roofing platform. Own positioning, GTM strategy, messaging, sales enablement, launch and content strategy, market intelligence, and AI-enabled workflows. Build and mentor a small team while operating hands-on to drive win rates, sales velocity, product adoption, and scalable revenue-focused marketing systems.

Provide technical advisory and solution feasibility analysis for enterprise AI initiatives. Evaluate AI engineering approaches, integration complexity, reusable components, and architectural tradeoffs. Support prototyping guidance, vendor capability evaluation, and surface governance, risk, and technical constraints to inform enterprise decisions.

Designs and integrates approved AI/ML tools into intelligence workflows by evaluating and configuring tools, redesigning processes, building prompt libraries and templates, measuring performance with KPIs, applying Lean Six Sigma improvements, and driving analyst adoption through training and stakeholder collaboration.

The AI Engineer will develop user-facing features using TypeScript and React, collaborate on product ideas, and leverage AI coding tools in a high-velocity team environment.

Seeking a Senior AI Engineer to develop AI solutions, oversee project delivery, and collaborate on system architecture. Requires 5+ years with Python and AI technologies.

As a Product Engineer, you'll collaborate on AI solutions for expert sourcing, client portals, and autonomous agents, driving product vision and coding.

The AI Machine Learning Engineer will design, develop, and deploy AI/ML solutions, ensuring compliance with federal standards and improving operational efficiency.

Design, build, and scale the AI platform for distributed multi-GPU training, experiment tracking, and model deployment. Optimize GPU clusters, networking (NCCL/InfiniBand), Kubernetes-native scheduling, and inference serving (TensorRT, Triton). Develop agentic automation for cluster health, CI/CD, and data curation while integrating ML lifecycle tooling and observability.

Develop Python-based ML components for spatial data quality, design robust software, and collaborate in an Agile environment.

Lead commercial origination and conversion of GPU compute demand for Armadas AI factory and Leviathan deployments. Build qualified pipelines, match customer requirements to sites and configurations, structure offtake and reservation deals, manage strategic accounts, and feed market intelligence into capacity planning and go-to-market decisions. Collaborate with legal, finance, product, and infrastructure teams to turn demand into committed capacity.

The Senior Manager of AI Innovation leads AI/ML research for robotics, driving innovation projects and managing a team. Responsibilities include overseeing project lifecycles and ensuring successful AI technology deployment across robotic systems.

The Software Development Engineer II focuses on integrating AI technologies into geospatial software, developing tools for automation, and collaborating with teams for innovative features.