AI Forward Deployed Engineering (FDE) Intern

Univers; Singapore; On-site; SGD 13,392 - 20,088; Part time

Job summary

Univers invites an AI Forward Deployed Engineering Intern to join our Global Impact Lab in Singapore. You will work with AI scientists, engineers, product teams, and domain experts to translate real‑world challenges into AI use cases and practical solutions.

You’ll prototype, evaluate models, and support production‑ready systems, gaining hands‑on experience across research, engineering, and domain applications while learning how AI is deployed in complex environments.

Qualifications

• Currently pursuing a degree in Computer Science, AI, Data Science, or related field.
• Strong programming in Python; experience with ML frameworks preferred.
• Familiarity with ML, LLMs, CV, multimodal AI, and data science concepts.

Responsibilities

• Collaborate with AI scientists and engineers to develop prototypes and proofs‑of‑concepts.
• Explore modern AI technologies including LLMs, CV, multimodal AI, and AI agents.
• Build AI applications and intelligent workflows using enterprise data.
• Assist in evaluating foundation models for domain‑specific use cases.
• Translate operational challenges into clear technical AI solutions with guidance.
• Contribute to AI experiments, model evaluation, and rapid prototyping.
• Collaborate across research, engineering, product, and domain experts throughout development.

Skills

Python

PyTorch

Machine Learning

Large Language Models

Computer Vision

Multimodal AI

Data Science

Software Engineering

Education

Bachelor's/Master/PhD candidate

Tools

PyTorch

Job description

Univers provides the world’s most comprehensive decarbonization system.

We help companies and countries optimize energy systems and reduce carbon emissions with accurate, reliable, and actionable decarbonization data. Our EnOS (Energy and Environment Operating System) platform connects on-the-ground operational technology and in-the-cloud intelligence to deliver real-time energy data and data-driven carbon monitoring, reporting, and abatement.

With 365 million sensors and smart devices connected, 845 GW of renewable energy under management, and a community of over 500 customers, we’re helping the world’s leading businesses get the world to net zero—and what comes after it.

For more information, please visit https://univers.com/.

AI FDE Intern

Are you looking to build intelligent systems that move beyond digital experiments and into the physical world? The Univers Global Impact Lab was established to bring advanced AI into the physical world, helping organizations transform how they operate, optimize resources, and make better decisions. Our mission is to translate advances in AI into production‑grade systems that bridge enterprise systems and physical operations, empowering organizations to solve complex real‑world challenges through intelligent decisions and actions. We build AI that combines foundation models, multimodal data, operational intelligence, and intelligent agents to understand information from business systems alongside industrial assets, sensors, and operational workflows. AI is moving from promise to accountability. Enterprises are looking beyond AI demonstrations and expect intelligent systems that deliver measurable outcomes in real‑world operations. The Univers Global Impact Lab is helping build the foundation for Physical AI by bringing together perception, reasoning, and operational intelligence to turn real‑world signals into meaningful actions. If you are excited about applying AI to solve real‑world problems and want to learn how advanced AI moves from research into production, this is an opportunity to work alongside experienced scientists and engineers while contributing to projects that create measurable impact.

About the Role

As an AI Forward Deployed Engineering (AI FDE) Intern, you will work alongside AI scientists, engineers, product teams, and domain experts to develop AI solutions for real‑world operational challenges across industries. AI FDE is about turning ambiguous real‑world challenges into clear AI use cases, then applying advanced AI to build practical solutions that deliver measurable operational impact. You will learn how to understand complex operational challenges, identify the right AI opportunities, rapidly prototype solutions, and work across research, engineering, product, and domain expertise to deliver real‑world impact. Throughout the internship, you will contribute across the AI solution lifecycle, from understanding problems and exploring technical approaches to building prototypes, evaluating AI models, and supporting production‑ready solutions. This is a hands‑on opportunity to learn how modern AI systems are developed and deployed in real‑world environments.

Responsibilities

• Collaborate with AI scientists and engineers to develop AI prototypes and proof‑of‑concepts for real‑world use cases.
• Explore and apply modern AI technologies, including large language models, computer vision, multimodal AI, AI agents, and modern AI engineering techniques.
• Build AI applications, intelligent workflows, and agentic systems using enterprise, operational, and multimodal data.
• Assist in evaluating, adapting, and integrating foundation models for domain‑specific applications.
• Help translate ambiguous operational challenges into clear technical solutions with guidance from experienced team members.
• Contribute to AI experiments, model evaluation, benchmarking, and rapid prototyping.
• Collaborate with AI scientists, engineers, product managers, GTM teams, and domain experts throughout the solution development lifecycle.
• Contribute to technical documentation, demonstrations, presentations, and knowledge sharing.
• Continuously learn emerging AI technologies and explore how they can be applied to solve real‑world problems.

Qualifications

• Currently pursuing a Bachelor's degree (senior undergraduate), Master's degree, or Ph.D. candidate in Computer Science, Engineering, Artificial Intelligence, Data Science, Electrical Engineering, or a related field.
• Strong programming skills in Python; experience with PyTorch or similar machine learning frameworks is preferred.
• Technical background in one or more of the following areas: Machine Learning, Large Language Models, Computer Vision, Multimodal AI, Agentic Systems, Data Science, and Software Engineering.
• Experience through coursework, research, personal projects, hackathons, or previous internships is a plus.
• Strong analytical and problem‑solving skills.