Top Artificial Intelligence Jobs

Support FP&A for a dental practice management SaaS: build financial models, forecast ARR/MRR, automate reporting with BI and AI, analyze practice usage and pricing, integrate SAP/Salesforce data, and deliver executive dashboards and insights for product, sales, and operations.

Design, develop, deploy, and maintain AI/ML models and pipelines. Collaborate with cross-functional teams, implement MLOps and CI/CD, monitor model performance, investigate incidents, ensure compliance with security/privacy/ethical requirements, and document model architectures and procedures.

Develop and execute test plans for AI models; identify and analyze defects and anomalies; implement automated evaluation frameworks (dataset checks, API tests, CI/CD); define AI quality metrics (accuracy, latency, fairness, cost); collaborate with development teams to improve model performance; analyze test results and provide actionable recommendations to enhance model accuracy and reliability.

Design, develop, train, validate, and deploy AI/ML products for life-sciences customers. Advise leadership on technical and commercial feasibility, collaborate with cross-functional and commercial teams, and lead projects in RL, LLM agent harnesses, fine-tuning, governance, and model evaluation.

Lead design and training of large-scale transformer and hybrid foundation models across text and multimodal domains. Drive architecture choices (attention variants, MoE), optimize training stability and optimizers, validate scaling laws and compute/data tradeoffs, design loss and alignment strategies (RLHF, DPO, contrastive), and execute distributed training (FSDP, ZeRO-3, tensor/pipeline parallelism) with mixed precision and checkpointing while partnering with ML systems teams.

Lead and grow a team of AI Deployment Engineers to design, deploy, and scale secure, production-grade AI systems for enterprise customers. Own technical success across architecture, reliability, security, adoption, and expansion; act as senior technical escalation; partner cross-functionally to create reusable patterns, operating models, measurement, and product feedback loops while hiring and developing talent.

Design, implement, optimize, and maintain gameplay AI systems (enemies/NPCs) using Unreal Engine and C++. Collaborate with design and gameplay engineers, ship console/PC titles, mentor peers, write technical design documents, and integrate/maintain AI middleware and navigation/pathfinding systems.

Design, build, and operate the C3 Agentic AI Platform for production AI agents. Architect scalable, reliable distributed systems; improve agent accuracy, performance, and safety; implement guardrails, auditability, and rollback; collaborate with data scientists and product owners; own end-to-end projects and mentor junior engineers.

Hunter-oriented BDM responsible for sourcing and qualifying new enterprise and mid-market opportunities across North America, building pipelines, outbound prospecting, coordinating discovery, partnering with leadership to close deals, and attending events (travel ~40%). Focus on selling consulting and technology services.

Lead end-to-end UX for a diagnostic platform, translating complex clinical and operational workflows into scalable, accessible, data-dense interfaces. Collaborate with Product, Engineering, Clinical, and Compliance to prototype, validate, and ship solutions; mentor designers; use AI tools to accelerate design work; create design artifacts and systems; and ensure implementation quality across multiple test types and regulated environments.

Hunt and close new consulting engagements across North America for AI and cloud solutions. Build and manage pipeline, prospect outbound, qualify opportunities, coordinate discovery, partner with leadership to close deals, and attend industry events (travel ~40%).

Design, build, and maintain RAG/LLM-driven capabilities, vector search, and analytics products. Architect data pipelines, develop Next.js front ends and BI dashboards, integrate authentication and AI workflows, produce telemetry and performance reporting, and deliver production-ready solutions with minimal oversight while presenting insights to leadership.

Design and build enterprise data warehouse, scalable data pipelines, integrations (OneStream, Workday, Oracle, Databricks), and AI/agent solutions (RAG, vector stores). Partner with Finance/HR/Legal/IT to translate workflows into automated, secure, maintainable enterprise data and AI services, and support analytics and reporting.

The Marketing AI Engineer enhances marketing with AI tools, manages application integrations, tracks AI utilization goals, and fosters team enablement in a 4-month contract role.

Apply LLM-based tools and traditional analytics to operational data: ingest and curate data, automate recurring analyses, tune prompts/agents, deliver decision-support reporting, and convert ad-hoc requests into self-service tools for operations stakeholders.

Design, build, deploy, and operate production AI systems for Operations, including agents, evaluation pipelines, and shared frameworks. Develop advanced algorithms (optimization, forecasting, CV), design APIs/SDKs, ensure reliability/latency/cost targets, mentor junior engineers, and partner with IT/security for production readiness.

Build and optimize local LLM inference and agent runtimes for Windows and GeForce RTX GPUs. Profile and reduce latency/memory, integrate CUDA/TensorRT pipelines, implement sandboxed security and privacy routers, and harden multi-agent orchestration for constrained consumer hardware while collaborating across research, driver, and open-source teams.

Lead GPU and HPC cluster architecture and deployment for cloud partners: design end-to-end GPU/NVLink infrastructures, perform performance modeling, validate and debug cluster configurations, support NPI deployments, and serve as technical liaison between engineering, product, and field teams.

Build and scale AI-enabled Customer Success workflows and automations across lifecycle, health, renewal, and engagement. Prototype tools, connect data systems, establish prompt/QA processes, gather CSM feedback, and measure impact to improve productivity and consistency.

Lead Trustly's internal AI strategy and team to evaluate, adopt, and scale foundation models, agentic tooling, and LLM orchestration. Establish governance, partner across functions to prioritize AI features and automations, drive adoption and measurable ROI, and evangelize AI capabilities company-wide.

Design, build, and maintain Trustly's internal AI platform and agentic workflow tooling. Partner with product and engineering teams to embed LLM-powered capabilities, lead prototyping and model evaluations, establish evaluation standards for quality and safety, and create reusable libraries, patterns, and enablement resources to drive internal AI adoption.

Lead and deliver large-scale AI and automation projects from planning through execution. Translate business goals into actionable plans, manage cross-functional stakeholders, risks, and dependencies, drive AI evaluation programs, improve workflows and SOPs, track project metrics, partner with technical teams on automation, and mentor project coordinators.

Lead design and implementation of AI-ready data platforms and scalable batch/streaming pipelines to support Generative AI and RAG solutions. Own architecture, reliability, governance, observability, and operationalization of production GenAI data systems across cloud environments. Mentor engineers and collaborate cross-functionally to integrate AI data products into enterprise workflows.

Lead Applied AI strategy and execution across Employee Benefits and Operations, overseeing ML, generative and agentic AI, RAG, and predictive analytics lifecycles. Drive governance, model risk management, evaluation, deployment, cross-LOB prioritization, talent architecture, and regulatory readiness to improve enrollment, billing, service, and operational efficiency.

Lead and coordinate technical AI and digital transformation projects across data, model, and platform domains. Translate architecture into project plans, manage cross-functional dependencies, enforce CI/CD and observability, oversee testing and compliance (regulatory and security), create runbooks and incident response, and ensure audit-ready evidence and controlled production cutovers.