Top Artificial Intelligence Jobs

Reliability Engineering Intern supporting manufacturing operations and maintenance through equipment criticality strategies, preventive maintenance and condition-monitoring routes, PM optimization, and root cause analysis. The role offers hands-on experience with corn wet milling, refining, reliability processes, sensors, AI, and manufacturing technologies. Interns will collaborate with operations and maintenance teams while developing technical communication, critical thinking, data analytics, and equipment performance skills.

Build and deploy AI/ML tools for GeForce NOW SRE operations, transforming production data, metrics, logs, and signals into incident root-cause analysis and operational forecasts. Lead LLM- and agent-based systems, develop large-scale data pipelines, optimize LLM workflows, and recommend sustainable AI platforms and architectures. The role also involves automation, Kubernetes, AWS cloud environments, monitoring, visualization, and production SRE practices.

Build and deploy production-grade AI applications for enterprise clients. Translate business requirements into solutions using Python, LLMs, RAG, AI agents, LangChain or similar frameworks, vector retrieval, and modern web technologies. Develop backend services and user-facing applications, integrate enterprise APIs and IAM systems, deploy with cloud platforms, Docker, and CI/CD, and optimize application quality, security, latency, reliability, and business performance. The role is full-time, remote, client-facing, and requires strong stakeholder communication.

Provides strategic legal counsel on privacy, data protection, cybersecurity, artificial intelligence, technology transactions, and digital innovation. Drafts and negotiates technology, cloud, software, data-sharing, and vendor agreements; supports incident response and breach investigations; develops privacy governance programs; reviews new technologies and products; manages regulatory matters; and advises executives and cross-functional teams on legal and technology risks.

Build and deploy scalable AI/ML systems for retrieval, ranking, categorization, triage, and generative AI across healthcare data. Own solutions end-to-end from problem framing and model selection through production deployment and optimization. Collaborate with software engineers, product managers, clinicians, and operations teams to translate complex business problems into explainable, maintainable systems with measurable outcomes.

Conduct applied AI research focused on explainability, reinforcement learning, retrieval-augmented generation, and long-context retrieval. Design, train, and evaluate machine learning models using large-scale healthcare data and distributed infrastructure. Build research prototypes and experimentation frameworks, validate measurable impact, and collaborate with ML Engineering, MLOps, and Product teams to transition innovations into production.

Own the roadmap and delivery of internal data platform products supporting clinical trial model development. Partner with engineering and scientific teams to understand workflows, prioritize improvements, write requirements, guide technical tradeoffs, measure outcomes, and drive adoption. The role requires hands-on data exploration, technical product management, and end-to-end ownership of platform improvements that accelerate model delivery.

Acquire and convert new enterprise accounts for networking, security, and cloud solutions across the Chicago territory. Own the full sales cycle, from prospecting and qualification through executive engagement, business-value assessments, closing, partner collaboration, and forecasting. Use AI-enabled sales intelligence, CRM, and sales platforms to build pipeline, personalize outreach, improve deal execution, and maintain forecast accuracy. The role requires a proven hunter mindset, C-level relationship building, complex enterprise selling, and consistent quota achievement.

Tenure-track faculty member specializing in robotics, automation, autonomous systems, or embodied AI. Responsibilities include developing an externally funded research program, teaching inclusive undergraduate and graduate courses, mentoring students, supervising research, participating in faculty governance, and contributing professional and public service. Research may address robot control, sensing, perception, manipulation, mobility, human-robot interaction, manufacturing, aerospace, medical robotics, agriculture, and space robotics.

Design AI-enhanced learning experiences and sales enablement programs for global sales teams. Build simulations, personalized learning paths, performance support, and automated feedback tools using modern AI and authoring technologies. Partner with Sales Leadership, Product Marketing, and Revenue Operations to align learning with seller competencies, launches, and sales methodologies. Measure learning impact through adoption, ramp time, performance, and quota attainment while establishing ethical AI design practices.

Own Rox’s engineering and builder talent community through hackathons, meetups, events, technical content, talent mapping, referrals, alumni programs, and campus relationships. Coordinate engineering leaders’ event presence, nurture prospective candidates, represent the company publicly, and translate engineering culture into scalable community programs. The role requires engineering fluency, strong writing, market-mapping ability, high ownership, and familiarity with the AI-native builder ecosystem.

Leads Bamboo’s architecture team and establishes enterprise architecture standards, roadmaps, governance, and reusable patterns across Guidewire, cloud, digital applications, integrations, and AI solutions. Manages and develops architects, guides architecture throughout delivery, evaluates technologies and vendors, and partners with engineering, product, security, DevOps, and business stakeholders. Oversees scalable, secure, observable, resilient solutions, including API and event-driven integrations, Guidewire modernization, and responsible generative AI adoption.

Own end-to-end data ingestion and extraction projects for government transportation clients. Translate statements of work into project plans, manage milestones and deliverables, coordinate data readiness and engineering environments, and serve as the primary client contact. Partner with state DOTs, MPOs, cities, and counties to deliver implementations on schedule and within scope while communicating technical progress to nontechnical stakeholders.

Serves as the Chief Commercial Officer’s strategic partner, overseeing global operating rhythm, governance, commercial roadmaps, executive communications, leadership reviews, and cross-functional initiatives. Represents the CCO in internal and external forums, aligns Sales, Product, Marketing, and Finance stakeholders, resolves organizational issues, and improves commercial workflows through AI-enabled tools and automation. Requires extensive experience in corporate strategy, business operations, consulting, or Chief of Staff/COO roles within SaaS, travel technology, or airline IT.

Drive end-to-end delivery of cloud technology and AI-enablement programs. Coordinate Product, Engineering, Information Security, Corporate Services, vendors, and business partners; manage requirements, timelines, dependencies, milestones, risks, and implementation plans. Facilitate workshops and status reviews, support roadmap prioritization and estimation, resolve blockers, and communicate program progress and technical delivery risks to stakeholders and senior leadership.

Build and scale backend platforms, orchestration systems, and user-facing capabilities powering Microsoft 365 Copilot. Collaborate with applied scientists and engineers to deliver scalable AI features, define architectures, create implementation plans, ensure robust testing, and improve engineering practices. Work spans enterprise-scale AI infrastructure, multimodal and agentic interactions, model capabilities, and production-ready intelligent systems.

Participate in the Gradient Development Program, complete technical training, pursue Google Cloud certifications, and collaborate with technical and business leads to translate business requirements into effective AI and machine learning solutions.

Three-month summer internship supporting physical system design and analysis using CAE tools, simulation workflows, Python scripting, and AI applications. The intern will assist with engineering analysis, data processing, reporting, professional services, project delivery, and customer-ready technical outputs while collaborating with application engineers and technical experts.

Entry-level application engineering role for recent engineering graduates in a cohort-based development program. Participants rotate through technical sales, customer support, training, and professional services while using Cadence CAE tools for physical-system simulation and analysis. Responsibilities include coding and scripting with Python, troubleshooting customer problems, developing solutions and demonstrations, supporting projects, creating engineering outputs, and applying artificial intelligence to engineering workflows and customer service.

Make outbound calls for B2B technology companies, engage gatekeepers and decision-makers, and book qualified meetings for customer sales teams. Use an AI-enabled platform for lead lists, dialing, call preparation, and coaching. Contractors choose their schedules and accounts, complete training and certification, follow approved scripts, and earn commission based on attended qualified meetings.

Develops data science solutions for an intelligence community agency by integrating disparate data, performing exploratory and quantitative analysis, creating visualizations and dashboards, and applying machine learning to produce actionable insights. The role requires Python, SQL, ETL, data communication skills, and TS/SCI clearance. Preferred experience includes Apache Spark, JEMA, Flask, JavaScript, cloud services, APIs, geospatial data, and supervised or unsupervised machine learning.

Research and develop quantum sensing, materials, and qubit-control technologies for quantum computing, communications, and sensing applications supporting the DoD. Conduct advanced laboratory experiments, analyze complex datasets, evaluate results, recommend technical solutions, provide direct customer support, communicate scientific concepts, and mentor teammates. The role requires quantum research expertise, scientific publications, a master’s degree, and eligibility for TS/SCI clearance.

Leads Salesforce consulting engagements from sales through delivery, overseeing project teams, solution architecture, staffing, governance, client relationships, and executive stakeholder alignment. Develops scopes, estimates, SOWs, and growth plans; guides Salesforce and contact center transformations; ensures quality delivery and customer satisfaction; and provides thought leadership on AI agents, Agentforce, and emerging technologies. Travel up to 25% is required.

Leads enterprise AI fluency and organizational change management initiatives. Responsibilities include identifying AI integration opportunities, designing adoption and governance models, overseeing scalable learning and upskilling programs, supporting client presales, managing stakeholders, measuring behavioral and business outcomes, and embedding change enablement into technology implementations. The role requires strategic and tactical leadership across functions while adapting curriculum, guardrails, and operating models to evolving AI capabilities.

Leads enterprise automation consulting and delivery from requirements gathering through design, scripting, testing, deployment, and support. Partners with business and IT stakeholders, assesses automation benefits, develops frameworks and process improvements, manages cross-functional initiatives, documents solutions, resolves production issues, and mentors colleagues. The role also evaluates emerging AI and machine learning use cases, supports technical standards, manages automation lifecycle activities, and communicates automation strategy and value to technical and business leadership.