Top Artificial Intelligence Jobs

Develops production-grade AI and machine-learning solutions, including LLM integrations, end-to-end pipelines, autonomy algorithms, testing, deployment, monitoring, and continuous improvement. Translates business and mission requirements into solution architectures, integrates AI capabilities into applications, and collaborates with stakeholders on adoption and innovation. Requires Python, machine-learning lifecycle knowledge, generative AI experience, REST API integration, and familiarity with MLOps, cloud, containerization, and knowledge-graph technologies.

Leads exploratory data analysis, statistical research, predictive modeling, and scalable AI solution development. Applies machine learning, deep learning, visualization, cloud computing, GPU processing, and distributed systems to deliver business insights and operational improvements. Translates operational needs into AI architectures, leads software development teams, integrates models into production, and communicates recommendations to stakeholders. The role also involves model validation, data governance, CI/CD, project planning, and stakeholder negotiation.

Lead reliability improvements for AI development and deployment platforms through software engineering, automation, observability, testing, and incident-response enhancements. Own reliability initiatives from design through implementation and adoption, standardize CI/CD, GitOps, progressive delivery, and telemetry practices, and develop reusable tooling for health validation and recovery. Integrate and test autonomous hardware and software systems, coordinate verification and validation, analyze test results, mentor engineers, and collaborate across teams.

Develops and deploys AI, machine learning, autonomy, and generative-AI solutions for mission systems and enterprise applications. Builds end-to-end pipelines, integrates LLM capabilities, implements perception and planning algorithms, and supports requirements, software development, testing, troubleshooting, and deployment. Collaborates with stakeholders, researches emerging technologies, and contributes to human-machine interfaces, MLOps, knowledge graphs, and cloud-based AI solutions.

Leads and executes software-intensive programs focused on AI-enabled mission applications, autonomy, command and control, and tactical systems. Integrates advanced technologies across multidisciplinary teams, develops software in C++, Java, and Python, and uses CI/CD, containers, Linux, and agile tools. Applies AI/ML optimization techniques, supports safety-critical solutions, develops technical proposals, and leads teams toward mission-critical objectives.

Serves as the senior hardware expert for autonomous systems, designing and integrating sensors, compute, storage, controls, wiring, and embedded components. Supports hardware-software integration, system safety, certification, deployment, testing, and field operations. Develops hardware solutions for autonomous ground vehicles, performs electrical debugging, creates test procedures and verification software, and ensures designs meet architecture and program requirements. The role also provides technical leadership for FPGA, wiring harness, autonomy platform, and long-duration field-test activities.

Develops, integrates, tests, and deploys AI, machine learning, autonomy, perception, planning, and control algorithms for mission systems. Translates requirements into production-grade machine-learning pipelines and software, integrates generative AI and LLM capabilities, troubleshoots implementations, and supports research-driven innovation. Collaborates with stakeholders, documents interfaces, develops human-machine interaction scenarios, and advances enterprise AI adoption.

Develops, integrates, tests, and deploys autonomy, AI, and machine learning algorithms for mission systems. Leads technical and multidisciplinary engineering efforts, delivers production AI systems using LLMs and generative AI, and supports the full software lifecycle from requirements through implementation. Responsibilities include perception, planning, controls, human-machine interfaces, cloud deployment, troubleshooting, mentoring engineers, and guiding technical projects.

Develops, integrates, tests, and deploys AI, machine learning, autonomy, perception, planning, controls, and human-machine interface capabilities for mission systems. Translates requirements into production software, builds LLM and generative AI systems with agentic workflows, troubleshoots integrations, and supports the full development lifecycle. The role requires Python, React, TypeScript, cloud platforms, containerization, and software engineering practices.

Develops, integrates, tests, and deploys autonomy, AI, machine learning, and agentic automation algorithms for mission systems. Translates requirements into software, supports perception, planning, controls, human-machine interfaces, and troubleshooting throughout the development lifecycle. Builds RPA and LLM-driven workflows using Python, automation frameworks, graph databases, ontology engineering, and CI/CD practices. Manages automation projects, documents technical solutions, and collaborates with stakeholders to deliver scalable solutions.

Develop and deploy scalable Generative AI and machine learning solutions for engineering workflows. Responsibilities include identifying AI opportunities, building prototypes and production applications, designing LLM retrieval and agentic workflows, integrating APIs and data, implementing testing and monitoring, and applying cybersecurity, DevSecOps, architecture, and responsible AI governance. The role partners with engineering, architecture, data, and IT teams to mature secure enterprise AI capabilities.

Supports the application of AI and machine learning to supply chain forecasting, optimization, and automation. Responsibilities include assisting with ML model development and validation, preprocessing supply chain data, feature engineering, evaluating model performance against operational KPIs, and supporting data-driven decision-making and responsible AI integration.

Researches and develops AI, machine learning, computer vision, signal processing, and control algorithms for autonomous defense and commercial systems. Builds, trains, evaluates, and optimizes models; develops prototypes and data products; defines requirements; and collaborates across perception, mission planning, simulation, testing, and customer application teams.

Researches and develops AI and machine learning algorithms for autonomous defense and commercial systems. Designs, prototypes, integrates, tests, troubleshoots, and optimizes software supporting perception, mission planning, motion planning, controls, and signal processing. Applies modern machine learning and deep learning techniques, interfaces with multidisciplinary teams, and documents requirements and implementations. The role also involves DevOps deployment, database integration, Linux development, and communication of complex technical concepts.

AI and supply chain intern supporting machine learning applications for forecasting, optimization, and automation. Responsibilities include preprocessing supply chain data, developing or validating predictive models, engineering features, evaluating model performance against operational KPIs, and supporting data-driven decision-making. The intern will learn supply chain AI/ML fundamentals, responsible AI integration, and enterprise operational workflows while gaining experience in analytics, reporting, and cross-functional communication.

Develops, integrates, tests, and deploys autonomy, artificial intelligence, and machine learning algorithms for mission systems. Responsibilities include perception, motion and mission planning, controls, software design, requirements translation, model implementation, troubleshooting, debugging, human-machine interface development, and test evaluation across the technology development lifecycle.

Develops, integrates, tests, and deploys autonomy, artificial intelligence, and machine learning algorithms for mission systems. Responsibilities include translating requirements into software, implementing perception, planning, controls, and human-machine interfaces, training models, troubleshooting defects, evaluating test results, and supporting the full technology development lifecycle.

Develops, integrates, tests, and deploys autonomy, artificial intelligence, and machine learning algorithms for mission systems. Responsibilities include requirements translation, software design, model training and evaluation, perception and planning functionality, human-machine interfaces, troubleshooting, debugging, and lifecycle support. The role requires advanced technical expertise, software engineering capabilities, and collaboration across development and integration activities.

Hands-on technical leader who designs, builds, and deploys production-grade AI automation and agentic workflows. Responsibilities include rapid prototyping, RAG and document-intelligence systems, API integrations, orchestration, monitoring, reusable AI assets, and mentoring a small engineering team to deliver frequent releases and measurable business impact.

Develop and deploy scalable full-stack web applications with AI-powered features. Build responsive frontends, backend services, REST APIs, databases, authentication, chatbots, automation tools, and intelligent workflows. Integrate LLMs, AI APIs, machine learning models, RAG, embeddings, and AI agents. Optimize performance, security, reliability, and scalability while testing and deploying through CI/CD pipelines. Collaborate with product, design, and engineering teams in a fully remote environment.

Lead development of a hybrid physics-AI foundation model for Full Waveform Inversion using real seismic data. Integrate AI into seismic imaging pipelines, scale solutions across GPUs, HPC systems, and 3D datasets, and validate performance on complex field data. Develop production-grade scientific software, establish robustness and risk metrics, collaborate with stakeholders, mentor team members, and drive adoption of modern AI/ML methods.

Designs, builds, and deploys enterprise AI applications using Anthropic Claude, RAG, agents, tool use, and governed enterprise data. Develops Databricks, Spark, PySpark, Python, SQL, and Delta Lake pipelines supporting AI workloads. Defines production architectures, integrations, evaluation frameworks, guardrails, monitoring, security, and responsible AI practices. Collaborates with business, data, security, governance, and engineering teams while mentoring engineers and optimizing solutions for reliability, scalability, performance, and cost.

Leads forward-deployed AI engineering within business delivery pods, translating ambiguous workflows into production agentic systems. Designs multi-agent workflows, RAG pipelines, integrations, security controls, HITL interfaces, evaluations, and guardrails. Builds prototypes, connects agents to banking systems, establishes engineering standards, reviews architecture and code, mentors engineers, and contributes reusable components to enterprise AI platforms.

Build and maintain end-to-end applications using React, Golang, and Node.js. Leverage AI development tools to improve speed and quality, collaborate with product and design, contribute to deployment and DevOps, and own features from concept through release. The role requires proactive problem-solving, rapid learning, scalable system design, and a strong builder’s mindset in a fast-paced energy and logistics technology environment.

Lead the architecture, strategy, and development of enterprise generative AI initiatives. Define AI/ML standards, guide scalable model deployment, conduct advanced research, and collaborate with executives, product, data science, and engineering teams. Mentor technical leaders, promote MLOps and responsible AI practices, optimize models for cost and performance, and represent the organization through publications and industry engagement.