Top Artificial Intelligence Jobs

Identifies and delivers AI and data science use cases that improve digital experiences, content personalization, member engagement, and staff efficiency. Leads AI pilots, model deployment, monitoring, data integration, governance, and responsible AI practices. Collaborates with IT, data leadership, and business stakeholders to translate technical solutions into measurable value and educate staff on AI capabilities.

Unpaid AI engineering internship to design, build, and deploy ML solutions (NLP, computer vision, recommenders). Work on data preprocessing, model training/fine-tuning, containerized FastAPI microservices, and scalable deployments on Google Cloud Run. Contribute to code reviews, GitHub repos, and integration of third-party AI APIs.

Design and optimize a cloud-native cybersecurity data lakehouse to support ML and GenAI workloads. Build feature store and vector DB architectures, high-throughput APIs and connectors, enable distributed compute for training/inference, and collaborate with Data Science and MLOps to productionize models and automate pipelines.

Participants are needed for an AI technology research study, offering compensation up to $600 for ~1.5-2 hours of participation over one week, requiring skills in tech-related roles.

Lead architecture and implementation of a patient-controlled health data platform: custody, consent management, secure EHR integrations, AI-native workflows (LLMs, agents, RAG), mobile-first patient experiences, and build the engineering culture and hiring bar as a founding technical partner.

Lead design, training, and deployment of large-scale ML models (LLMs, diffusion, GNNs). Own end-to-end training pipelines, distributed training, and evaluation. Collaborate with data and infra teams, drive architecture and inference decisions, and provide technical leadership and mentorship.

Owns enterprise customer deployments from discovery and workflow design through execution, go-live, and long-term success. Leads customer discovery, translates business processes into AI agent workflows, coordinates with delivery engineers and internal teams, configures and tests agent solutions, and manages deployment plans, risks, timelines, scope changes, escalations, and executive communications. The role also improves scalable onboarding processes and requires significant client interaction and travel.

Own customer deployments from discovery and workflow design through execution, launch, and ongoing success. Lead customer discovery, translate business processes into AI agent workflows, configure and test agent setups, manage deployment plans and risks, coordinate stakeholders, lead customer meetings, handle scope changes and escalations, and improve repeatable onboarding processes. The role is client-facing, onsite, early-career, and requires approximately 25–30% travel.

Provides remote executive and operational support for coaching engagements. Responsibilities include tracking client engagements, managing calendars and deliverables, drafting follow-ups, preparing coaching documents, administering business software access, maintaining digital files, and supporting executives. The role also researches and optimizes AI workflows using Claude and Gemini for document generation, transcript analysis, and automation, while coordinating multiple concurrent priorities with minimal supervision.

Build and deploy autonomous AI agents and GenAI solutions at scale. Design and operationalize distributed data flows, agent orchestration, memory/RAG systems, and integrations with LLM APIs. Collaborate globally, prototype state-of-the-art ML/GenAI technologies, and ensure scalable, reliable cloud-native architectures.

Participants complete guided AI research activities onsite, including walking, sitting, gestures, photos, audio recordings, and video recordings. The study takes 2.5–5 hours and requires no prior experience. Applicants must be ages 13–75+, speak English, and be authorized to work in the United States. Minors need parental or legal guardian consent.

Design, train, deploy, and optimize deep learning and computer vision models for semiconductor inspection systems. Develop production-quality algorithms combining deep learning with physics-based modeling or signal processing, manage datasets and evaluation pipelines, and improve inference performance using GPU and high-performance computing. Collaborate across engineering teams and support deployments at customer sites, including occasional international travel.

Design and implement large-scale, distributed AI-driven SD-WAN systems and real-time, fault-tolerant services. Drive features end-to-end from design through testing and deployment, improve scalability and operability, participate in code and design reviews, and collaborate with product and documentation teams.

Lead the architecture, prototyping, deployment, and scaling of agentic AI platforms for NVIDIA Marketing. Translate marketing opportunities into reliable AI agents, reusable platform capabilities, and production architectures. Establish practices for evaluation, observability, security, governance, reliability, and cost optimization while partnering with engineers on integrations, tooling, retrieval, memory, orchestration, and infrastructure. Guide complex initiatives from discovery through ongoing operations and communicate technical solutions to technical and business stakeholders.

Responsible for acquiring new customers and managing sales processes for software solutions in the Life Sciences industry, achieving growth through upselling and strategic presentation efforts.

Lead development of data infrastructure, analytics platforms, and data products; deploy predictive and diagnostic models (ML/AI); drive consumer, marketing, business, and operational insights; manage large global teams; partner with IT and cross-functional leaders to inform product, sales, and marketing strategy and enable data-driven decision making.

Lead Americas Procurement digital solutions team to build reporting, automations, systems support, data governance, and AI/ML enablement. Prioritize project intake, deliver Power BI and Oracle-based solutions, drive process automation and adoption, and track business impact while coaching and developing team capability.

The Enterprise Data Architect develops and optimizes database solutions, migrating data, conducting tests, and ensuring information system functionality.

Supports an insider risk program by developing AI, data science, and cybersecurity solutions. Analyzes large and unstructured datasets to identify insider threats, anomalies, and emerging AI risks. Builds statistical and machine learning models, ensures data quality and governance, creates reports and visualizations, and advances security operations, processes, and tools. The role collaborates with senior stakeholders, mentors analysts, and translates threat insights into proactive defensive and offensive security capabilities.

12-month graduate programme based in Dubai delivering hands-on experience in employee benefits analytics, pricing and risk modelling. Work with data, BI platforms and modelling tools to build pricing models, dashboards, forecasts, and automation; learn insurance policy design, regulation, and insurer engagement before transitioning to a permanent role.

Lead client-facing data science work: design and develop ML/AI solutions, build and monitor operational data pipelines, query/migrate data via APIs, use SQL/NoSQL and cloud architectures, guide teammates, and translate complex data into actionable insights. Requires TS/SCI with polygraph and extensive data science experience.

Perform data exploration, cleaning, analysis, and visualization on structured and unstructured data. Develop predictive models and machine learning algorithms, apply distributed/data-processing tools, collaborate with clients, and lead solution development. Support deliverables, travel up to 25%, and obtain required security clearance.

Lead data science projects to extract insights from structured and unstructured data using AI/ML and IoT. Work with clients, guide teams, develop algorithms and systems, process geospatial and varied file formats, build visualizations, and deliver data-driven recommendations.

Sell tax/trade software solutions into large enterprise accounts in the PA territory. Prospect and build pipeline, develop and execute account plans, manage full sales cycle from outreach to close and renewal, maintain Salesforce CRM, collaborate cross-functionally, and meet revenue targets. Requires travel (25-50%).

Lead quality engineering for manufacturing cells: develop and audit inspection/testing processes, analyze statistical data, drive corrective actions and continuous improvement, mentor staff, coordinate PCAB and present program risks. Ensure compliance with quality standards and work cross-functionally with suppliers, engineering, and manufacturing.