AI Engineering Intern: Build Scalable Production ML

QuantCo; Philippines; Remote; PHP 1,200,000 - 1,800,000; Full time

Benefits offered by this job

Stock options

Relocation support

Location-based benefits

Job summary

QuantCo is building AI engineers to design, test, and deploy AI systems embedded at scale across enterprise settings. You will lead data and inference pipelines, orchestrate RAG-based components, and balance engineering constraints with business priorities to deliver production-ready solutions.

You will collaborate with data scientists and clients, working across the product lifecycle from design to deployment to drive impactful AI applications in real-world environments.

Qualifications

• PhD/ MSc/ BSc in CS, engineering, physics or related STEM from a leading university.
• Experience with CV, NLP, or Graph Neural Networks.
• Proficient in Python programming.
• Familiarity with Gemini, OpenAI, and Anthropic APIs and advanced features.
• Understanding of LLM inference considerations and token usage.
• Strong CS fundamentals: data structures, cloud, distributed systems, ML, HPC.
• Experience with large, unstructured real-world datasets.

Responsibilities

• Design, test, and deploy AI systems embedded at scale.
• Lead the design of data and inference pipelines and integrate RAG components.
• Balance engineering constraints with business priorities and deploy end-to-end solutions.
• Collaborate with clients and cross-functional teams to iterate and deploy AI solutions.

Skills

Python programming

LLM inference

APIs (Gemini/OpenAI/Anthropic)

Structured outputs & tool calling

Data structures

Cloud infrastructure

Distributed systems

Unstructured data handling

Education

BSc, MSc or PhD in Computer Science, Engineering, Physics, or related STEM field

Tools

Gemini API

OpenAI API

Anthropic API

Job description

QuantCo is building AI engineers to design, test, and deploy AI systems embedded at scale across enterprise settings. You will lead data and inference pipelines, orchestrate RAG-based components, and balance engineering constraints with business priorities to deliver production-ready solutions.

You will collaborate with data scientists and clients, working across the product lifecycle from design to deployment to drive impactful AI applications in real-world environments.