Artificial Intelligence Engineer

Columbia University is seeking skilled analytics professionals to join us as part-time Adjunct Associate Faculty for a graduate-level course on Artificial Intelligence of Things (AIOT) starting in Fall 2026. This role provides an exceptional opportunity to engage in graduate-level teaching while contributing subject matter expertise and supporting the instructional process.The course aims to equip students with a thorough understanding of IoT technologies and their integration with AI and robotics. Participants will delve into IoT architecture, critical components, and communication protocols, and will gain hands-on experience with IoT platforms, sensors, and data acquisition devices. The curriculum emphasizes practical AIOT applications for real-time decision-making in various sectors, including manufacturing, public safety, smart cities, and healthcare, while also addressing ethical considerations associated with these technologies.Through a combination of conceptual learning and practical assignments, the course features weekly lectures, readings on IoT fundamentals, and biweekly quizzes to evaluate understanding. Students will apply their knowledge through individual assignments and a collaborative term project, ensuring a solid foundation in IoT analytics and AI-driven robotic automation.

Join the School of Professional Studies at Columbia University as an Adjunct Lecturer for our graduate-level course in Artificial Intelligence of Things (AIOT), commencing in Fall 2026. We are seeking seasoned industry professionals passionate about sharing their expertise in this rapidly evolving field.This course offers an in-depth exploration of IoT technologies and their integration with AI and robotics. Engage students in critical discussions about IoT architecture, essential components, and communication protocols, while providing them with practical experience using IoT platforms, sensors, and data acquisition tools. The curriculum focuses on real-world AIoT applications that facilitate immediate decision-making in sectors such as manufacturing, public safety, smart cities, and healthcare, while also addressing the ethical implications of these innovative technologies.Blending theoretical knowledge with hands-on assignments, the course includes weekly lectures, readings on the fundamentals of IoT, and biweekly assessments to evaluate student comprehension. Participants will demonstrate their understanding through individual assignments and a collaborative term project, laying a strong foundation in IoT analytics and AI-driven robotic automation.

Columbia University is actively seeking qualified professionals to join our team as part-time Adjunct Associate Faculty for the graduate-level course titled Introduction to Blockchain, Cryptocurrencies & Analytics. This course is designed to impart essential knowledge about blockchain technology and cryptocurrencies to our Master of Science students in Applied Analytics. Topics covered will include cryptographic protocols, hashing, digital signatures, transaction chaining, decentralization through proof of work mining, and smart contracts.The role of an Adjunct Associate Faculty member is pivotal for providing expertise and facilitating the learning process within the course. This position offers an excellent opportunity to gain valuable experience in graduate-level education at Columbia University.

Columbia University is seeking experienced analytics professionals to join our faculty as part-time Adjunct Associate Faculty for a graduate-level course titled Analytics for Cybersecurity Management. This role offers a unique opportunity to contribute your subject matter expertise and support the instructional process for aspiring cybersecurity leaders. Engaging in this capacity will provide valuable exposure to the academic environment at Columbia University.This course serves as a comprehensive introduction to foundational cybersecurity principles, including network security, threat detection, and vulnerability management. It emphasizes the transformative impact of emerging technologies such as AI and machine learning on modern defense strategies. Participants will engage with key frameworks and advanced tools through real-world case studies, gaining insights into the role of analytics in effective threat intelligence, incident response, and regulatory compliance.Students will enhance their practical skills through hands-on exercises and interactive assignments, culminating in a project focused on automating vulnerability analysis. They will learn critical tasks such as log parsing, vulnerability classification, dashboard visualization, and AI-driven anomaly detection, while also addressing ethical, legal, and regulatory issues in cybersecurity. By the conclusion of the course, participants will be equipped to design proactive defense measures and adeptly navigate diverse threat landscapes, leveraging AI and analytics to bolster digital security against evolving cyber threats.Key ResponsibilitiesAttend all class sessions, assist with instruction, lead breakout sessions, and facilitate engaging discussions.Evaluate and grade student assignments and assessments as directed by the course Lecturer.Monitor student progress and address any concerns or inquiries in a timely manner.

The School of Professional Studies at Columbia University is actively seeking seasoned industry professionals to join our academic team as part-time Adjunct Associate Faculty for a graduate-level course in Cloud Computing. This position provides a unique opportunity to contribute to the instructional process while gaining valuable experience in graduate-level teaching at Columbia University.The Cloud Computing course is designed to expose analytics students to practical applications and concepts of cloud computing, including infrastructure, administration, and various services and applications. Emphasis will be placed on developing hands-on skills for utilizing cloud services to create distributed and scalable analytics applications.Key ResponsibilitiesParticipate in all class sessions, support instructional delivery, lead breakout sessions, and facilitate engaging discussions.Assess and grade student submissions and evaluations as mandated by the course Lecturer.Address and manage student inquiries and concerns proactively.

The Applied Analytics program at Columbia University is excited to invite seasoned data analytics professionals to join our team as a part-time Associate Faculty  for the graduate-level course Applied Deep Learning and AI. This advanced course immerses students in deep learning concepts, integrating essential components from Statistical Machine Learning. Participants will establish a robust foundation in supervised learning alongside various algorithms and methodologies. Key topics include Support Vector Machines, Neural Networks, Convolutional Neural Networks (CNN), word embeddings, attention mechanisms, transformers, encoder-decoder architectures, Generative Adversarial Networks (GAN), and Reinforcement Learning. Practical applications will provide students with insights on preparing, training, testing, and validating models.An Associate Faculty member plays a pivotal role in delivering subject matter expertise and enhancing the instructional experience for course participants. This position offers an exceptional opportunity to gain invaluable exposure to graduate-level teaching within the prestigious environment of Columbia University.Responsibilities:Attend and engage in all on-campus class sessions, assist with instruction, lead breakout discussions, and facilitate student engagement.Evaluate and assess student work as directed by the course Lecturer.Address student inquiries and concerns proactively.Conduct regular office hours for student support.

Columbia University is on the lookout for analytics professionals to join as part-time Adjunct Associate Faculty for an advanced course on Applied Generative AI in Fall 2026. This role offers an incredible opportunity to gain firsthand experience in graduate-level teaching while contributing to the academic community.The Applied Generative AI course introduces students to the fascinating field of generative modeling, a vital aspect of machine learning. Participants will explore theoretical foundations, practical applications, and gain hands-on experience using high-level APIs and open-source foundational models. The curriculum covers essential methodologies for employing, fine-tuning, and programmatically working with cutting-edge Generative AI tools. Students will also delve into the intricacies of low-level model implementations, empowering them to train and understand models based on their data, from foundational principles. Various generative models, including Variational Autoencoders (VAEs), Generative Adversarial Networks (GANs), and Transformers, will be examined, with applications spanning text, image, audio, and video generation.Key ResponsibilitiesParticipate in all class sessions, assist with instructional duties, lead breakout sessions, and facilitate engaging discussions.Assess and grade student assignments and evaluations as directed by the course Lecturer.Address student inquiries and concerns in a timely and supportive manner.

The School of Professional Studies at Columbia University is inviting applications for the role of Adjunct Associate Faculty for a graduate-level course titled Analytics for Business Operations Management, starting in the Fall of 2026. This part-time position offers a unique opportunity to engage in graduate-level teaching while contributing to the academic community at one of the world's leading institutions.This course aims to equip students with analytical techniques to enhance operational decision-making, increase efficiency, and tackle real-world challenges in operations management. Enrolled students will gain hands-on experience in key topics including process analysis, forecasting, queuing theory, simulation, optimization, inventory analysis, project management, supply chain management, and lean operations. By combining lectures with practical coding exercises, the course fosters a comprehensive understanding applicable across various industries.Key Responsibilities:Participate in all class sessions, assist with instruction, and lead breakout discussions.Deliver lectures and facilitate engaging classroom discussions.Assess and grade student assignments as directed by the course Lecturer.Address student inquiries and concerns promptly.

Columbia University is seeking skilled analytics professionals to join our faculty as a part-time Adjunct Associate for the graduate-level course Mathematics for AI. As an Adjunct Associate, you will provide essential subject matter expertise and support the instructional process for this course section, gaining valuable exposure to graduate-level teaching at Columbia University.Key Responsibilities:Participate in all class sessions, assist with teaching, and lead breakout sessions to enhance student engagement.Deliver class lectures and facilitate discussions, ensuring a rich learning environment.Assess and grade student assignments and assessments as requested by the course Lecturer.Monitor student inquiries and concerns, providing timely support and guidance.

The School of Professional Studies at Columbia University is on the lookout for a dedicated data analytics professional to join us as a part-time Adjunct Associate Faculty in our graduate course, Applied Analytics Frameworks & Methods I.In today's data-driven world, vast amounts of information are generated at unprecedented speeds through business transactions, online interactions, social media, and various sensors. This influx provides unique opportunities for predicting outcomes and understanding phenomena across diverse fields, including medicine, business, and space exploration. Our course emphasizes supervised learning techniques that facilitate effective predictions and insights. Students will navigate the data-wrangling process, starting with data exploration and foundational methodologies, before diving into supervised learning techniques such as linear regression, decision trees, and support vector machines. Additionally, students will engage in a predictive analytics competition to apply and integrate their learning.As an Adjunct Associate Faculty member, you will play a pivotal role in supporting the instructional process and providing subject matter expertise. This position is an excellent opportunity to gain experience in graduate-level teaching at Columbia University.Key ResponsibilitiesAttend all scheduled class sessions, assist with instruction, lead breakout sessions, and facilitate discussions.Evaluate and grade student work and assessments as directed by the course Lecturer.Address and respond to student concerns and inquiries.

Columbia University invites accomplished analytics professionals to join as part-time Adjunct Associate Faculty for the graduate-level course on Managing Data. This position offers a unique opportunity to gain firsthand experience in graduate-level teaching while providing critical subject matter expertise. As an Adjunct Associate Faculty member, you will support the instructional process and engage with students in a dynamic learning environment.The Managing Data course equips students with essential skills for effective data management, enabling them to leverage data confidently in collaboration with technology teams. The curriculum addresses the challenges posed by diverse data languages and techniques, offering a comprehensive overview of data technologies, database engines, foundational principles, governance processes, and organizational requirements to ensure data quality.Key ResponsibilitiesAttend all class sessions, assist in instructional activities, lead breakout sessions, and facilitate engaging discussions.Evaluate and grade student assignments and assessments as directed by the course Lecturer.Address student inquiries and concerns promptly and effectively.

Join our team at Columbia University as a part-time Adjunct Associate Faculty for an advanced course on AI User Interfaces for Analytics. This role offers analytics professionals an exceptional opportunity to contribute their expertise while gaining valuable experience in graduate-level education at one of the leading institutions in the world.Key ResponsibilitiesParticipate in all class sessions, assist with instructional delivery, lead breakout discussions, and engage students in meaningful dialogue.Conduct class lectures and oversee instructional activities, ensuring a conducive learning environment.Assess and grade student assignments and assessments as required.

The School of Professional Studies at Columbia University is actively seeking qualified candidates for the role of Adjunct Associate Faculty in the graduate-level course on Financial Securities Analysis and Portfolio Management. This part-time position offers a unique opportunity for individuals to gain valuable experience in graduate-level instruction at one of the nation's premier educational institutions.This course delves into the intricate world of financial securities, equipping students with the analytical tools necessary to evaluate financial assets and devise effective investment strategies. It serves as a comprehensive introduction to key investment topics that are crucial for those pursuing careers in investment analysis or portfolio management.Key Responsibilities:Participate in all class sessions, assist in instructional duties, lead breakout discussions, and facilitate engaging classroom interactions.Deliver lectures, oversee instructional activities, and actively participate in classroom conversations.Assess and grade student assignments and evaluations as directed by the course Lecturer.Address student inquiries and concerns, providing support and guidance throughout the course.

Normal Computing | Transformative OpportunitiesAt Normal Computing, we are at the forefront of innovation, developing the essential software and hardware that propel technology forward. Our contributions support the semiconductor industry and critical AI infrastructures, impacting the systems that power our everyday lives. Our collaborative team spans across dynamic cities including New York, San Francisco, Copenhagen, Seoul, and London.Your Role in Our Vision:We are in search of an AI Engineer to create production systems capable of interpreting extensive technical documents, such as chip design specifications, and transforming them into executable code. You will deliver tangible improvements to our customers on a weekly basis, while exploring the cutting-edge possibilities of AI in hardware through reinforcement learning, agentic coding, and superior software engineering practices.Key Responsibilities:Oversee the entire AI development lifecycle from initial concept to production deployment and iterative enhancements.Develop and implement solutions powered by large language models (LLMs) to derive insights from intricate technical specifications.Navigate multi-modal complexities and investigate multi-agent and reinforcement learning methodologies for generating agentic code and utilizing tools effectively.Formulate strategies aimed at managing latency, output variance, and ensuring robust error handling at scale.Collaborate with product and engineering teams to seamlessly integrate AI functionalities into our platform.Mentor junior engineers and set best practices for AI development.What Makes You Ideal for This Role:Demonstrable experience in deploying production-level AI systems involving language models, particularly those focused on document comprehension and agentic workflows.Strong software engineering background with experience in distributed systems and production-quality code.Proficient in Python and contemporary machine learning frameworks such as PyTorch, Hugging Face, and Transformers.Hands-on expertise in prompt engineering, fine-tuning, and deploying large language models.Aptitude for managing, cleaning, and preprocessing large-scale, diverse datasets.Familiarity with AI safety, bias mitigation, and ethical considerations.Ability to articulate complex AI concepts to both technical and non-technical audiences.Bonus Qualifications:Experience with deploying AI systems in production settings, especially in the context of document understanding.

Role overview Adonis seeks a Director of Artificial Intelligence to lead its AI and machine learning strategy. This executive position combines advanced technical expertise with healthcare experience, guiding the direction, development, and oversight of AI initiatives throughout the organization. The Director will play a key role in ensuring Adonis delivers compliant and effective AI solutions for healthcare clients. AI is central to Adonis’s mission of improving financial outcomes in healthcare. The company values curiosity, rigor, and integrity in its approach, aiming to achieve measurable results for both internal teams and clients. In this role, the Director will define the vision for how AI powers Adonis’s revenue cycle management products, with a focus on helping healthcare providers recover more revenue, reduce manual work, and build scalable, intelligent financial systems. Main responsibilities AI strategy and vision: Create and carry out an AI/ML strategy that aligns with business goals and healthcare industry needs. Incremental value delivery: Balance long-term AI projects with near-term initiatives that produce real results in revenue cycle management. Team leadership: Mentor and guide Data Science and Machine Learning teams, fostering a culture of innovation and high standards. AI governance and compliance: Build and maintain an AI governance framework to ensure all solutions meet healthcare regulatory requirements, such as HIPAA and FDA guidelines. Solution architecture: Design scalable, production-ready AI and ML systems that deliver value to healthcare customers. Demonstrating value: Clearly communicate the benefits of Adonis’s AI solutions to customers, partners, and stakeholders. MLOps best practices: Promote effective processes for deploying, monitoring, and maintaining AI models in production. Cross-functional collaboration: Work closely with Product, Engineering, and other teams to integrate AI into company initiatives. Location This position is based in New York City.

iCapital is revolutionizing the alternative investment landscape with our innovative financial technology platform. Our solutions have redefined how advisors, wealth management firms, asset managers, and banks assess and recommend personalized public and private market strategies for their affluent clients. As of June 2025, iCapital manages approximately $945 billion in global client assets across 1,940 funds. Recognized by Forbes as a leading Fintech company for seven consecutive years (2018-2024), we have also been acknowledged as one of the Best Startup Employers by Forbes (2021-2023) and a four-time recipient of the MMI/Barron’s Solutions Provider award.

Role Overview CurbWaste is looking for a Head of Artificial Intelligence based in New York, NY. This leader will guide the company’s AI efforts and help shape the future of waste management through advanced technology. What You Will Do Set and refine the AI strategy to align with CurbWaste’s business goals Lead the development and deployment of machine learning models to improve operations and customer experience Work closely with teams across the company to integrate AI solutions into products and services Promote data-driven decision-making throughout the organization Who We’re Looking For This role calls for a leader with a vision for how AI can transform waste management. Experience in building and scaling AI initiatives is important, as is the ability to collaborate across functions and inspire teams to adopt new technologies.

The School of Professional Studies at Columbia University is seeking passionate and qualified professionals to join our team as part-time Adjunct Lecturer for a graduate-level course titled Mathematics for Artificial Intelligence. This course empowers students with critical mathematical skills necessary for comprehending and utilizing artificial intelligence (AI) algorithms. By the conclusion of the course, students will be equipped with a robust mathematical toolkit to adeptly navigate the challenges posed by contemporary AI algorithms.Key Responsibilities:Facilitate engaging class lectures, instructional activities, and dynamic classroom discussions. Attendance at all class sessions is mandatory.Provide support to students by monitoring and addressing their concerns and inquiries.Assess and grade student assignments and evaluations.Hold regular office hours for student consultations.

We are seeking a visionary Director of Applied AI to lead our innovative projects at Metropolis, headquartered in the vibrant city of New York. In this pivotal role, you will drive the development and implementation of cutting-edge AI solutions that enhance our operations and deliver transformative results across various sectors.Your leadership will inspire a talented team of data scientists and engineers as you collaborate with cross-functional partners to translate complex data into actionable insights. You will be responsible for setting the strategic direction of our AI initiatives, ensuring alignment with our business objectives, and fostering a culture of continuous improvement and innovation.