Top Artificial Intelligence Jobs

Develop, research, optimize, and deploy computer vision AI/ML algorithms for remote sensing, including automatic target recognition and multimodal EO/SAR data fusion. Responsibilities include processing large datasets, training supervised and unsupervised deep learning models, deploying solutions to cloud environments, reviewing research, documenting capabilities, and potentially leading junior engineers. The role requires an active TS/SCI clearance and supports defense and commercial applications.

Supports the sales process as the primary technical advisor for Infinera’s telecommunications products. Develops and delivers technical presentations, demonstrations, quotations, and RFI/RFP responses; interprets customer requirements; designs and cost-models solutions; supports marketing events and after-sales activities; and builds long-term customer relationships. The role requires expertise in optical, DWDM, long-haul, metro, access, mobile backhaul, and fronthaul systems, along with strong communication and presentation skills.

Supports the development and deployment of production AI systems by fine-tuning and evaluating machine learning models, integrating AI features, working with training and evaluation data, running experiments, monitoring performance, and collaborating with engineering and product teams. Requires current enrollment in a relevant bachelor's or master's program, Python proficiency, familiarity with PyTorch or TensorFlow, and foundational machine learning knowledge.

Define the vision, roadmap, and priorities for AI-powered products. Translate customer needs and ambiguous AI capabilities into product requirements and user experiences, partnering with engineering, research, design, sales, and marketing to launch and improve products. Use customer feedback, usage data, and performance metrics to drive iteration and product value.

Build and scale AI medical scribe features using LLMs, develop responsive web and iOS experiences, and maintain audio-processing, cloud, and EHR integration infrastructure. Lead projects from concept to production, collaborate with product and design teams, and work directly with customers to gather feedback and rapidly improve the product.

Own the enterprise AI technical strategy, including model, vendor, platform, architecture, cost, security, and reliability evaluations. Establish AI standards, reference architectures, governance processes, and usage and spend visibility. Advise executives and engineering teams, assess AI risks, and partner with Risk, Compliance, and Legal. Prototype and validate LLM, API, agent, and RAG capabilities through working code, scaling productive experiments into reliable organizational capabilities.

Build and ship AI-native frontend experiences using React, Next.js, TypeScript, and Tailwind. Architect scalable frontend systems, reusable components, state management, API integrations, and performance optimizations. Own user-facing features end to end, bridge AI capabilities with intuitive interfaces, and collaborate across product, design, and backend engineering. Rapidly prototype with AI tools while maintaining high standards for accessibility, visual polish, responsiveness, and production quality.

Own AI product areas from discovery through launch, defining problems, writing PRDs, building prototypes, conducting customer research, partnering with engineering and design, and establishing success metrics. The role requires translating complex generative AI capabilities into useful enterprise workflow experiences, accounting for probabilistic behavior and model failure modes, and shipping technically complex products with measurable outcomes.

Design and ship backend services powering multimodal AI agents, including data ingestion, APIs, storage, background processing, orchestration, evaluation frameworks, and deployment architecture. Build reliable AI workflows with structured outputs, tool calling, state management, grounding, and guardrails. Own enterprise security, tenant isolation, auditability, scalability, and technical direction while partnering cross-functionally and mentoring engineers.

Build and deploy backend services powering multimodal AI agents, including data ingestion, storage, APIs, background processing, orchestration pipelines, and deployment architecture. Develop reliable AI workflows with evals, guardrails, structured outputs, tool calling, state management, and grounding. Design secure, observable, scalable systems with tenant isolation and auditability. Partner across engineering, product, design, AI, and infrastructure to ship enterprise-grade features quickly.

Build and ship production frontend features for AI-native enterprise workflows. Develop React UI components, integrate backend APIs, work within component libraries, and learn scalable frontend architecture, state management, performance optimization, and advanced React patterns. Collaborate with designers and backend engineers, use AI development tools, iterate based on user feedback, and receive mentorship from senior engineers.

Build and ship AI tools from prototype to adoption across partner communities. Own technical architecture, build-versus-partner decisions, privacy-safe deployments, testing, bias control, governance, and scale strategy. Manage technology and funding partnerships, pursue AI program opportunities, develop go-to-market budgets, and present recommendations to executive and board audiences. Translate tools into practitioner documentation and training while ensuring human oversight and data dignity.

Leads the design, development, deployment, and sustainment of production AI agents and AI-enabled applications. Defines agent architectures, integrates enterprise and geospatial data with LLMs using RAG and MCP, and guides Node.js and Oracle Database application development. Provides hands-on technical leadership, mentors developers, reviews engineering work, establishes practices, and coordinates delivery across mission, data, cloud, security, database, and customer stakeholders.

Develop, train, evaluate, deploy, and maintain computer vision and machine learning models for warfighter performance and visual defect or anomaly detection. Translate operational needs into maintainable ML solutions, design validation strategies, optimize model thresholds, and integrate inference into software systems. Collaborate with data engineers, data scientists, architects, subject matter experts, and product owners while communicating technical findings and tradeoffs.

Own Pursuit’s data infrastructure, semantic layer, data dictionary, reporting, dashboards, and AI-enabled capabilities. Improve data quality and self-service access while designing structures with cross-functional teams. Establish data governance for reliable human and AI-agent use, evaluate AI workflows, integrate SaaS systems, and administer permissions and workflows. The role requires hands-on technical work, cross-functional project management, stakeholder communication, and high ownership of scalable data systems.

Build and deploy production AI/ML features across the model lifecycle, including GenAI systems, RAG pipelines, data pipelines, evaluation infrastructure, and MLOps. Apply machine learning to manufacturing, supply chain, computer vision, predictive maintenance, forecasting, inventory, and logistics problems. Collaborate with engineering, manufacturing, and operations teams to deliver measurable outcomes.

Serve as a pre-sales technical advisor helping public-sector and GovTech customers integrate Claude. Design scalable AI and cloud architectures, guide evaluations and deployments, explain technical concepts to diverse stakeholders, support Claude products, and collaborate with Sales, Product, and Engineering. The role requires frequent customer-site travel, strong enterprise communication skills, and experience with technical customer-facing work, cloud systems, Python, and LLM technologies.

Leads the selection, configuration, implementation, and ongoing management of safety technology across operating companies. Administers Procore safety workflows, manages Proxxi wearable devices, evaluates AI and emerging safety tools, monitors usage and data quality, develops training and rollout plans, tracks effectiveness and ROI, and manages technology vendors. Partners with safety, IT, operations, and field leadership to improve adoption and translate safety technology data into actionable recommendations.

Administers and expands safety technology platforms, including Procore and Proxxi wearable devices. Configures workflows, trains users, monitors adoption and safety data, evaluates emerging AI tools, manages vendors, and develops implementation plans and effectiveness metrics. Partners with safety, IT, operations, and company leadership to integrate technology across operating companies and translate data into actionable insights. The role is primarily office-based with periodic job-site travel.

Software Engineer Interns will help develop, test, and operate integrated cloud services supporting AI-powered hardware products. Responsibilities include collaborating with hardware, AI, platform engineering, and infrastructure teams; contributing to AI assistant and conference room device projects; solving software problems independently and collaboratively; and communicating across teams to deliver reliable solutions.

Develop and deploy advanced data science, machine learning, generative AI, and intelligent agent solutions across Salesforce and enterprise platforms. Build predictive models, conversational AI, data pipelines, and autonomous workflows for customer engagement, sales, and service operations. Partner with business and technical teams to define use cases, operationalize responsible AI, govern models, and deliver measurable outcomes. The role also involves evaluating emerging technologies, communicating insights to executives, mentoring developers, and establishing reusable technical standards.

Leads global strategy and commercial development for BMS’s neurodegeneration portfolio across discovery through Phase 3. Owns brand planning, forecasting, market development, biomarker and diagnosis strategy, launch preparation, and long-range planning for Alzheimer’s, Parkinson’s, DLB, and related assets. Partners cross-functionally across development, medical, regulatory, access, pricing, analytics, and commercial teams while engaging advocates, societies, agencies, and thought leaders. Builds organizational presence, guides stage-gate decisions, represents products to executive management, and leads commercial teams.

Own the financial services product line from discovery through launch and iteration. Set the roadmap, determine which deployment capabilities become core product features, conduct user discovery, define quality standards, and establish accuracy, human-review, citation, and safe-failure models for regulated workflows. Prototype in design or code, collaborate with engineers and designers, understand the market, and deliver reusable AI capabilities across financial institutions.

Lead Moloco’s global product marketing strategy across its AI advertising portfolio. Own product naming, positioning, messaging, enablement, content, thought leadership, website strategy, launches, and product storytelling. Build the product marketing operating model, integrate marketing into the product lifecycle, partner with product and go-to-market teams, manage segment and geographic marketing, lead a high-performing team, and represent Moloco publicly on AI advertising and industry trends.

Lead Legora's cloud and AI partner strategy and relationships, build and run co-sell motions, manage marketplace presence, develop joint GTM plans, drive partner-sourced pipeline into sales, and feed partner insights into Product and GTM.